{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# matplotlib基础绘图 2\n",
    "## 直方图\n",
    "### 基础绘图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.12 0.21 0.03 0.12 0.09 0.03]\n",
      "0.6\n",
      "1.6666666666666667\n",
      "1.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "data = [1, 1, 9, 1, 3, 5, 8, 2, 1, 5, 11, 8, 3, 4, 2, 5, 5, 2, 2, 2, 7, 11]\n",
    "n_bins = 6\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "num, bins, patches = plt.hist(data, n_bins, density=True, histtype='bar', range=(0, 10),\n",
    "                                 facecolor='#99cc33', alpha=0.75, rwidth=0.6, ec=\"k\")\n",
    "print(num)  # 频率/组距\n",
    "print(sum(num))  # 频率/组距之和\n",
    "print((max(bins)-min(bins))/n_bins)  # 组距\n",
    "print(sum(num)*(max(bins)-min(bins))/n_bins)  # 频率/组距之和*组距\n",
    "\n",
    "plt.title('Histogram')\n",
    "plt.xlabel('value')\n",
    "plt.xticks(bins, bins)\n",
    "plt.ylabel('frequency')\n",
    "plt.grid(True)\n",
    "\n",
    "plt.savefig(r'figs\\figure1.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 864x504 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习1\n",
    "import matplotlib.pyplot as plt\n",
    "infile = open(r\".\\files\\assembly.fas\", 'r')\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "for seq_line in infile:\n",
    "    if seq_line[0] != \">\":\n",
    "        data += [len(seq_line.strip())]\n",
    "infile.close()\n",
    "# 将序列的长度分成10组，绘制直方图\n",
    "# 在下面写你的代码#\n",
    "\n",
    "# 在上面写你的代码#\n",
    "plt.savefig('figs/ex1.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 201.   354.6  508.2  661.8  815.4  969.  1122.6 1276.2 1429.8 1583.4\n",
      " 1737. ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习1-答案\n",
    "import matplotlib.pyplot as plt\n",
    "infile = open(\"./files/assembly.fas\", 'r')\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "for seq_line in infile:\n",
    "    if seq_line[0] != \">\":\n",
    "        data += [len(seq_line.strip())]\n",
    "infile.close()\n",
    "# 将序列的长度分成10组，绘制直方图\n",
    "# 在下面写你的代码#\n",
    "n_bins = 10\n",
    "num, bins, patches = plt.hist(data, n_bins, density=True, histtype='bar',\n",
    "                                 facecolor='#cc3300', alpha=0.75, rwidth=0.95, ec=\"k\")\n",
    "print(bins)\n",
    "plt.title('Histogram')\n",
    "plt.xlabel('length')\n",
    "plt.xticks(list(map(int, bins)), list(map(int, bins)))\n",
    "plt.ylabel('frequency')\n",
    "plt.grid(False)\n",
    "# 在上面写你的代码#\n",
    "plt.savefig('figs/ex1.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 864x504 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习2\n",
    "import matplotlib.pyplot as plt\n",
    "infile = open(\"./files/assembly.fas\", 'r')\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "for seq_line in infile:\n",
    "    if seq_line[0] != \">\":\n",
    "        data += [len(seq_line.strip())]\n",
    "infile.close()\n",
    "\n",
    "# 将序列的长度按照组距200分组，绘制直方图\n",
    "# 在下面写你的代码#\n",
    "\n",
    "# 在上面写你的代码#\n",
    "\n",
    "plt.savefig('figs/ex2.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习2-答案\n",
    "import matplotlib.pyplot as plt\n",
    "infile = open(\"./files/assembly.fas\", 'r')\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "for seq_line in infile:\n",
    "    if seq_line[0] != \">\":\n",
    "        data += [len(seq_line.strip())]\n",
    "infile.close()\n",
    "\n",
    "# 将序列的长度按照组距200分组，绘制直方图\n",
    "# 在下面写你的代码#\n",
    "n_bins = (max(data)-min(data))//200+1\n",
    "num, bins, patches = plt.hist(data, n_bins, density=True, histtype='bar',\n",
    "                                 range=(min(data)//200*200, (max(data)//200+1)*200),\n",
    "                                 facecolor='#3300cc', alpha=0.75, rwidth=0.45, ec=\"k\")\n",
    "plt.title('Histogram')\n",
    "plt.xlabel('length')\n",
    "plt.xticks(list(map(int, bins)), list(map(int, bins)))\n",
    "plt.ylabel('frequency')\n",
    "plt.grid(True)\n",
    "# 在上面写你的代码#\n",
    "\n",
    "plt.savefig('figs/ex2.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 通过直方图推导概率密度函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[6.49350649e-05 1.62337662e-04 3.89610390e-04 1.13636364e-03\n",
      " 2.17532468e-03 4.51298701e-03 8.01948052e-03 1.54220779e-02\n",
      " 2.12337662e-02 2.67857143e-02 3.37012987e-02 3.75324675e-02\n",
      " 5.09090909e-02 3.32792208e-02 2.84090909e-02 2.23701299e-02\n",
      " 1.56493506e-02 1.09415584e-02 5.97402597e-03 3.18181818e-03\n",
      " 1.39610390e-03 9.41558442e-04 2.92207792e-04 1.62337662e-04\n",
      " 3.24675325e-05]\n",
      "0.3246753246753248\n",
      "3.08\n",
      "1.0000000000000002\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAswAAAGfCAYAAABLI4TeAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAGWtJREFUeJzt3X+QXedd3/HPt9bEKczggKO0lq0gU5u0TgppUA3ulPyBm8auaYSLNShlimeq1mVat6UdpjgTkwHX/JHSGU87GKinSuO6bWzkVFStBYYSBtqOMVbITxNcFBOQWBUUbMyE1AmCb/+4V/Wy3n32arV3f1iv18yO7p773KNnH+9abx2de051dwAAgOX9ic2eAAAAbGWCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAAzs2ewJLvfa1r+09e/Zs9jQAAHiF+/CHP/zZ7t652rgtF8x79uzJ8ePHN3saAAC8wlXVr88yzikZAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABjYsdkTAGB5t+6/JQunT85l37uu2J0jhx+by74BXmkEM8AWtXD6ZO4+dMNc9n3vwSfmsl+AVyKnZAAAwMBMwVxVN1XVM1V1oqruWub5S6vqkenzT1bVnun2PVX1f6vqo9OPH13f6QMAwHytekpGVV2S5P4kb0tyKslTVXW0u3950bCDSZ7v7muq6kCS9yb5tulzn+7uN6/zvAEAYEPMcoT5+iQnuvvZ7v5ikoeT7FsyZl+SB6ePH01yY1XV+k0TAAA2xyzBfGWSxW/TPjXdtuyY7j6b5IUkl0+fu7qqPlJVP1dV33iB8wUAgA01y1UyljtS3DOOOZ3k9d39O1X1dUl+vKre2N2/98deXHVHkjuS5PWvf/0MUwIAgI0xyxHmU0l2L/r8qiQLK42pqh1JLkvyXHd/obt/J0m6+8NJPp3kq5f+Bt39QHfv7e69O3fuPP+vAgAA5mSWYH4qybVVdXVVvSrJgSRHl4w5muT26ePbknyou7uqdk7fNJiq+qok1yZ5dn2mDgAA87fqKRndfbaq7kzyeJJLkryvu5+uqnuSHO/uo0kOJXmoqk4keS6TqE6Stya5p6rOJvnDJN/Z3c/N4wsBAIB5mOlOf919LMmxJdves+jxi0n2L/O6Dyb54AXOEQAANo07/QEAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABiYKZir6qaqeqaqTlTVXcs8f2lVPTJ9/smq2rPk+ddX1eeq6rvXZ9oAALAxVg3mqrokyf1Jbk5yXZJ3VtV1S4YdTPJ8d1+T5L4k713y/H1JfuLCpwsAABtrliPM1yc50d3PdvcXkzycZN+SMfuSPDh9/GiSG6uqkqSqviXJs0meXp8pAwDAxpklmK9McnLR56em25Yd091nk7yQ5PKq+tIk35Pk+y98qgAAsPFmCeZaZlvPOOb7k9zX3Z8b/gZVd1TV8ao6fubMmRmmBAAAG2PHDGNOJdm96POrkiysMOZUVe1IclmS55J8fZLbqupfJHlNkj+qqhe7+4cWv7i7H0jyQJLs3bt3aYwDAMCmmSWYn0pybVVdneQ3kxxI8jeXjDma5PYkTyS5LcmHuruTfOO5AVX1fUk+tzSWAQBgK1s1mLv7bFXdmeTxJJckeV93P11V9yQ53t1HkxxK8lBVncjkyPKBeU4aAAA2yixHmNPdx5IcW7LtPYsev5hk/yr7+L41zA8AADaVO/0BAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADOzY7AkAbEe37r8lC6dPzmXfu67YnSOHH5vLvgE4f4IZYA0WTp/M3YdumMu+7z34xFz2C8DaOCUDAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGdmz2BADm4db9t2Th9Mm57HvXFbvnsl8AtibBDLwiLZw+mbsP3TCXfd978Im57BeArckpGQAAMOAIM8BFat6nrRw5/Nhc9g2w0QQzwEXKaSsAs3FKBgAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGJgpmKvqpqp6pqpOVNVdyzx/aVU9Mn3+yaraM91+fVV9dPrxsaq6dX2nDwAA87VqMFfVJUnuT3JzkuuSvLOqrlsy7GCS57v7miT3JXnvdPsnk+zt7jcnuSnJv6mqHes1eQAAmLdZjjBfn+REdz/b3V9M8nCSfUvG7Evy4PTxo0lurKrq7s9399np9lcn6fWYNAAAbJRZgvnKJCcXfX5qum3ZMdNAfiHJ5UlSVV9fVU8n+USS71wU0P9fVd1RVcer6viZM2fO/6sAAIA5mSWYa5ltS48Urzimu5/s7jcm+YtJ3lVVr37ZwO4Huntvd+/duXPnDFMCAICNMUswn0qye9HnVyVZWGnM9Bzly5I8t3hAd38qye8nedNaJwsAABttlmB+Ksm1VXV1Vb0qyYEkR5eMOZrk9unj25J8qLt7+podSVJVX5nkDUk+sy4zBwCADbDqFSu6+2xV3Znk8SSXJHlfdz9dVfckOd7dR5McSvJQVZ3I5MjygenL/3KSu6rqD5L8UZK/392fnccXAgAA8zDTJd66+1iSY0u2vWfR4xeT7F/mdQ8leegC5wgAAJvGnf4AAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADMx0WTkAOF+37r8lC6dPzm3/u67YnSOHH5vb/gHOEcwAzMXC6ZO5+9ANc9v/vQefmNu+ARZzSgYAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADLjTH7DhNuKWyQCwXgQzsOHcMhmA7cQpGQAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGdmz2BABgrW7df0sWTp+cy753XbE7Rw4/Npd9A9uLYAZg21o4fTJ3H7phLvu+9+ATc9kvsP04JQMAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgMvKAS8z72vbAsB2IpiBl3FtWwB4iVMyAABgQDADAMCAYAYAgIGZgrmqbqqqZ6rqRFXdtczzl1bVI9Pnn6yqPdPtb6uqD1fVJ6a/ftP6Th8AAOZr1WCuqkuS3J/k5iTXJXlnVV23ZNjBJM939zVJ7kvy3un2zyb5693955PcnuSh9Zo4AABshFmOMF+f5ER3P9vdX0zycJJ9S8bsS/Lg9PGjSW6squruj3T3wnT700leXVWXrsfEAQBgI8wSzFcmWXxB1lPTbcuO6e6zSV5IcvmSMd+a5CPd/YWlv0FV3VFVx6vq+JkzZ2adOwAAzN0swVzLbOvzGVNVb8zkNI2/t9xv0N0PdPfe7t67c+fOGaYEAAAbY5ZgPpVk8a25rkqysNKYqtqR5LIkz00/vyrJkSTf0d2fvtAJAwDARpolmJ9Kcm1VXV1Vr0pyIMnRJWOOZvKmviS5LcmHurur6jVJHkvyru7+X+s1aQAA2CirBvP0nOQ7kzye5FNJfqy7n66qe6rqHdNhh5JcXlUnkvzTJOcuPXdnkmuSfG9VfXT68bp1/yoAAGBOdswyqLuPJTm2ZNt7Fj1+Mcn+ZV53b5J7L3COAACwadzpDwAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABnZs9gQAYKu6df8tWTh9ci773nXF7hw5/Nhc9g2sL8EMACtYOH0ydx+6YS77vvfgE3PZL7D+BDNsQ/M+6gUAvEQwwzbkqBcAbBxv+gMAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwIBgBgCAAcEMAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgAHBDAAAA4IZAAAGBDMAAAwIZgAAGBDMAAAwsGOzJwAAF7Nb99+ShdMn57LvXVfszpHDj81l33AxEcwAsIkWTp/M3YdumMu+7z34xFz2Cxcbp2QAAMDATMFcVTdV1TNVdaKq7lrm+Uur6pHp809W1Z7p9sur6mer6nNV9UPrO3UAAJi/VYO5qi5Jcn+Sm5Ncl+SdVXXdkmEHkzzf3dckuS/Je6fbX0zyvUm+e91mDAAAG2iWI8zXJznR3c929xeTPJxk35Ix+5I8OH38aJIbq6q6+/e7+39mEs4AALDtzBLMVyZZ/PbdU9Nty47p7rNJXkhy+XpMEAAANtMswVzLbOs1jFn5N6i6o6qOV9XxM2fOzPoyAACYu1mC+VSS3Ys+vyrJwkpjqmpHksuSPDfrJLr7ge7e2917d+7cOevLAABg7mYJ5qeSXFtVV1fVq5IcSHJ0yZijSW6fPr4tyYe6e+YjzAAAsFWteuOS7j5bVXcmeTzJJUne191PV9U9SY5399Ekh5I8VFUnMjmyfODc66vqM0m+LMmrqupbkvzV7v7l9f9SAABg/c10p7/uPpbk2JJt71n0+MUk+1d47Z4LmB8AAGwqd/oDAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgQDADAMCAYAYAgIGZ7vQHzO7W/bdk4fTJuex71xW7c+TwY3PZNwCwPMEM62zh9MncfeiGuez73oNPzGW/AMDKnJIBAAADghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABjYsdkTAADm59b9t2Th9Mm57HvXFbtz5PBjc9k3bCWCGQBewRZOn8zdh26Yy77vPfjEXPYLW41TMgAAYEAwAwDAgGAGAIABwQwAAAOCGQAABgQzAAAMCGYAABgQzAAAMCCYAQBgwJ3+uOjM+zaxAMAri2DmouM2sQDA+XBKBgAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAIABwQwAAAOuwwwArNm8bwZ15PBjc9k3nA/BDACsmZtBcTFwSgYAAAwIZgAAGBDMAAAwIJgBAGBAMAMAwICrZLClzPPyRMnkEkUAAOdDMLOlzPPyRIlLFAEA588pGQAAMCCYAQBgQDADAMCAYAYAgAFv+gMAtrR5XkFp1xW7c+TwY3PZN68cghkA2NLmeQUlV09iFoKZ8zLvv+UDAGw1gpnz4m/5ALzSOOWD1QhmAOCi5mAQq3GVDAAAGJgpmKvqpqp6pqpOVNVdyzx/aVU9Mn3+yaras+i5d023P1NVb1+/qQMAwPytekpGVV2S5P4kb0tyKslTVXW0u3950bCDSZ7v7muq6kCS9yb5tqq6LsmBJG9MsivJf6+qr+7uP1zvL4QJb8oDAFhfs5zDfH2SE939bJJU1cNJ9iVZHMz7knzf9PGjSX6oqmq6/eHu/kKSX6uqE9P9OaFnTpyHBQBbjzcWbm+zBPOVSRb/Fz6V5OtXGtPdZ6vqhSSXT7f/wpLXXrnm2c7ZRhyd9cMCABefeR/QEuTzVd09HlC1P8nbu/vvTD//W0mu7+5/uGjM09Mxp6affzqTI8n3JHmiu//DdPuhJMe6+4NLfo87ktwx/fQNSZ5Zw9fy2iSfXcPrmLB+a2ft1s7arZ21Wztrd2Gs39pZu7Wb19p9ZXfvXG3QLEeYTyVZfPLqVUkWVhhzqqp2JLksyXMzvjbd/UCSB2aYy4qq6nh3772QfVzMrN/aWbu1s3ZrZ+3WztpdGOu3dtZu7TZ77Wa5SsZTSa6tqqur6lWZvInv6JIxR5PcPn18W5IP9eTQ9dEkB6ZX0bg6ybVJfnF9pg4AAPO36hHm6TnJdyZ5PMklSd7X3U9X1T1Jjnf30SSHkjw0fVPfc5lEdabjfiyTNwieTfIPXCEDAIDtZKY7/XX3sSTHlmx7z6LHLybZv8JrfyDJD1zAHGd1Qad0YP0ugLVbO2u3dtZu7azdhbF+a2ft1m5T127VN/0BAMDFzK2xAQBgYNsGc1W9pqoerapfqapPVdUNVfUVVfXTVfWr01+/fLPnudVU1Ruq6qOLPn6vqr7L2s2mqv5JVT1dVZ+sqg9U1aunb4h9crp2j0zfHMsSVfWPp+v2dFV913Sb77sVVNX7quq3q+qTi7Ytu1418a+r6kRVfbyq3rJ5M998K6zd/un33h9V1d4l4981XbtnqurtGz/jrWOFtfvB6Z+1H6+qI1X1mkXPWbupFdbun0/X7aNV9VNVtWu63c/sEsut36LnvruquqpeO/18w9dv2wZzkn+V5Ce7+88m+dokn0pyV5Kf6e5rk/zM9HMW6e5nuvvN3f3mJF+X5PNJjsTaraqqrkzyj5Ls7e43ZfIm2HO3gr9vunbPZ3KreBapqjcl+buZXJ/9a5N8c1VdG993I+9PctOSbSut182ZXIXo2kyuaf8jGzTHrer9efnafTLJ30jy84s3VtV1mfwcv3H6mh+uqks2YI5b1fvz8rX76SRv6u6vSfK/k7wrsXbLeH9evnY/2N1fM/0z978lOff+Lz+zL/f+vHz9UlW7k7wtyW8s2rzh67ctg7mqvizJWzO5Oke6+4vd/buZ3Ir7wemwB5N8y+bMcNu4Mcmnu/vXY+1mtSPJn6zJ9ca/JMnpJN+UyS3hE2u3kj+X5Be6+/PdfTbJzyW5Nb7vVtTdP5/JVYcWW2m99iX59z3xC0leU1VXbMxMt57l1q67P9Xdy90Ua1+Sh7v7C939a0lOZPIXu4vSCmv3U9Of22Ry996rpo+t3SIrrN3vLfr0S5Oce+OYn9klVvh/XpLcl+Sf5aW1SzZh/bZlMCf5qiRnkvy7qvpIVf3bqvrSJH+qu08nyfTX123mJLeBA0k+MH1s7VbR3b+Z5F9m8rfc00leSPLhJL+76A+TLX379030ySRvrarLq+pLkvy1TG5q5Pvu/Ky0XlcmWXxPXN+Hs7N25+dvJ/mJ6WNrN4Oq+oGqOpnk2/PSEWZrN4OqekeS3+zujy15asPXb7sG844kb0nyI939F5L8fvxT7nmZnmf7jiSHN3su28X0fNF9Sa5OsiuTowU3LzPUpWeW6O5PZXLqyk8n+ckkH8vk2uysj1pmm+/D2Vi7GVXVuzP5uf2P5zYtM8zaLdHd7+7u3Zms253TzdZuFdODK+/OS3/J+GNPL7Ntruu3XYP5VJJT3f3k9PNHMwno3zp3SH76629v0vy2g5uT/FJ3/9b0c2u3ur+S5Ne6+0x3/0GS/5zkL2XyT0Hnrmm+7O3fSbr7UHe/pbvfmsk/u/1qfN+dr5XW61QmR+zP8X04O2s3g6q6Pck3J/n2ful6tNbu/PynJN86fWztVvdnMjlA9bGq+kwma/RLVfWnswnrty2Dubv/T5KTVfWG6aYbM7mb4OJbdN+e5L9swvS2i3fmpdMxEms3i99I8g1V9SVVVXnp++5nM7klfGLtVlRVr5v++vpM3nz1gfi+O18rrdfRJN8xfef4NyR54dypG6zqaJIDVXVpVV2dyZuIfnGT57SlVNVNSb4nyTu6+/OLnrJ2q5i+ufmcdyT5leljP7Or6O5PdPfruntPd+/JJJLfMm3AjV+/7t6WH0nenOR4ko8n+fEkX57k8kzeOf6r01+/YrPnuRU/Mnmz2u8kuWzRNms329p9fyb/w/tkkoeSXJrJOfW/mMkbXg4nuXSz57kVP5L8j0z+gvGxJDdOt/m+W3m9PpDJufJ/kMkfFAdXWq9M/nny/iSfTvKJTK7ksulfwxZbu1unj7+Q5LeSPL5o/Luna/dMkps3e/5bcO1OZHK+6EenHz9q7WZeuw9O/7z4eJL/muTK6Vg/szOs35LnP5PktZu1fu70BwAAA9vylAwAANgoghkAAAYEMwAADAhmAAAYEMwAADAgmAEAYEAwAwDAgGAGAICB/wc6c52pGIX39gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "input_file = open(r\".\\files\\tree_height.txt\")\n",
    "x = list(map(float, [i for i in input_file]))\n",
    "input_file.close()\n",
    "\n",
    "# example data\n",
    "mu = np.mean(x)  # mean of distribution\n",
    "sigma = np.std(x, ddof=1)  # standard deviation of distribution\n",
    "n_bins = 25\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "# the histogram of the data\n",
    "num, bins, patches = plt.hist(x, n_bins, density=True, histtype='bar',\n",
    "                                 facecolor='#99cc33', alpha=0.75, rwidth=0.95, ec=\"k\")\n",
    "\n",
    "print(num)\n",
    "print(sum(num)) \n",
    "print((max(bins)-min(bins))/n_bins) \n",
    "print(sum(num)*(max(bins)-min(bins))/n_bins) \n",
    "\n",
    "plt.savefig('figs/figure2.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "input_file = open(\"./files/tree_height.txt\")\n",
    "x = list(map(float, [i for i in input_file]))\n",
    "input_file.close()\n",
    "\n",
    "# example data\n",
    "mu = np.mean(x)  # mean of distribution\n",
    "sigma = np.std(x, ddof=1)  # standard deviation of distribution\n",
    "n_bins = 25\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "# the histogram of the data\n",
    "num, bins, patches = plt.hist(x, n_bins, density=True, histtype='bar',\n",
    "                                 facecolor='#99cc33', alpha=0.75, rwidth=0.95, ec=\"k\")\n",
    "\n",
    "# add a 'best fit' line\n",
    "#y = ((1 / (np.sqrt(2 * np.pi) * sigma)) *\n",
    "#     np.exp(-0.5 * (1 / sigma * (bins - mu))**2))\n",
    "\n",
    "#plt.plot(bins, y, '--')\n",
    "\n",
    "x1 =np.arange(60,140,1)\n",
    "y1 = ((1 / (np.sqrt(2 * np.pi) * sigma)) *\n",
    "     np.exp(-0.5 * (1 / sigma * (x1 - mu))**2))\n",
    "plt.plot(x1, y1, '--')\n",
    "\n",
    "plt.xlabel('Height')\n",
    "plt.ylabel('Probability density')\n",
    "plt.savefig('figs/figure2.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 864x504 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习3\n",
    "import matplotlib.pyplot as plt\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "with open(\"./files/assembly.fas\", 'r') as infile:\n",
    "    for seq_line in infile:\n",
    "        if seq_line[0] != \">\":\n",
    "            data += [len(seq_line.strip())]\n",
    "\n",
    "# 假设序列长度的分布符合y=c/x+b，绘制密度趋势线\n",
    "# 在下面写你的代码#\n",
    "\n",
    "# 在上面写你的代码#\n",
    "\n",
    "plt.savefig('figs/ex3.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n",
      "9\n",
      "1.53 -0.00088\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习3-答案\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "plt.figure(figsize=(12,7))\n",
    "data = []\n",
    "with open(\"./files/assembly.fas\", 'r') as infile:\n",
    "    for seq_line in infile:\n",
    "        if seq_line[0] != \">\":\n",
    "            data += [len(seq_line.strip())]\n",
    "\n",
    "# 假设序列长度的分布符合y=c/x+b，绘制密度趋势线\n",
    "# 在下面写你的代码#\n",
    "n_bins = (max(data)-min(data))//200+1\n",
    "num, bins, patches = plt.hist(data, n_bins, density=True, histtype='bar',\n",
    "                                 range=(min(data)//200*200, (max(data)//200+1)*200),\n",
    "                                 facecolor='#99cc33', alpha=0.75, rwidth=0.95, ec=\"k\")\n",
    "\n",
    "b = ((bins[1]+bins[0])*num[0]-(bins[-1]+bins[-2])*num[-1])/(bins[0]+bins[1]-bins[-1]-bins[-2])\n",
    "c = (bins[1]+bins[0])/2*num[0] - b*(bins[1]+bins[0])/2\n",
    "x1 =np.arange(200,1800,1)\n",
    "y = (c/x1 + b)\n",
    "plt.plot(x1, y, '--')\n",
    "print(len(num))\n",
    "print(len(bins))\n",
    "plt.title('Histogram')\n",
    "plt.xlabel('length')\n",
    "plt.xticks(list(map(int, bins)), list(map(int, bins)))\n",
    "plt.ylabel('frequency')\n",
    "plt.grid(True)\n",
    "# 在上面写你的代码#\n",
    "print(c,b)\n",
    "plt.savefig('figs/ex3.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 柱状图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "nucleotides = [\"A\", \"G\", \"C\", \"U\"]\n",
    "\n",
    "counts = [\n",
    "    [606, 1024, 759, 398],\n",
    "    [762, 912, 639, 591], \n",
    "    ]\n",
    "\n",
    "plt.figure(figsize=(12,7))\n",
    "plt.title('RNA nucleotides in the ribosome')\n",
    "plt.xlabel('RNA')\n",
    "plt.ylabel('base count')\n",
    "\n",
    "x1 = [2.3, 4.0, 6.0, 8.0]\n",
    "x2 = [1.5, 3.5, 5.5, 7.5]\n",
    "#x2 = [x - 0.5 for x in x1]\n",
    "\n",
    "plt.xticks([1.75, 3.75, 5.75, 7.75], nucleotides)\n",
    "#plt.xticks([x - 0.25 for x in x1], nucleotides)\n",
    "\n",
    "plt.bar(x1, counts[0], width=0.8, color=\"#99cc33\", label=\"E.coli 23S\")\n",
    "plt.bar(x2, counts[1], width=0.8, color=\"#8080cc\", label=\"T.thermophilus 23S\")\n",
    "\n",
    "plt.legend()\n",
    "plt.axis([1.0, 9.0, 0, 1200])\n",
    "plt.savefig('figs/figure6.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 864x504 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习4\n",
    "# 显示三个样本碱基含量百分比的柱状图\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "nucleotides = [\"A\", \"G\", \"C\", \"U\"]\n",
    "# sample 1, sample 2, sample 3\n",
    "counts = [\n",
    "    [0.217438105, 0.367420165, 0.272335845, 0.142805884],\n",
    "    [0.262396694, 0.314049587, 0.220041322, 0.203512397],\n",
    "    [0.285547786, 0.269230769, 0.233100233, 0.212121212]\n",
    "    ]\n",
    "plt.figure(figsize=(12,7))\n",
    "# 在下面写你的代码#\n",
    "\n",
    "# 在上面写你的代码#\n",
    "plt.savefig('figs/ex6.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习4-答案\n",
    "# 显示三个样本碱基含量百分比的柱状图\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "nucleotides = [\"A\", \"G\", \"C\", \"U\"]\n",
    "# sample 1, sample 2, sample 3\n",
    "counts = [\n",
    "    [0.217438105, 0.367420165, 0.272335845, 0.142805884],\n",
    "    [0.262396694, 0.314049587, 0.220041322, 0.203512397],\n",
    "    [0.285547786, 0.269230769, 0.233100233, 0.212121212]\n",
    "    ]\n",
    "plt.figure(figsize=(12,7))\n",
    "# 在下面写你的代码#\n",
    "plt.title('RNA nucleotides in the ribosome')\n",
    "plt.xlabel('RNA')\n",
    "plt.ylabel('base freqs')\n",
    "x2 = [3.0, 6.0, 9.0, 12.0]\n",
    "x1 = [x - 0.5 for x in x2]\n",
    "x3 = [x + 0.5 for x in x2]\n",
    "plt.xticks(x2, nucleotides)\n",
    "plt.bar(x1, counts[0], width=0.5, color=\"#99cc33\", label=\"Sample 1\")\n",
    "plt.bar(x2, counts[1], width=0.5, color=\"#ffcc00\", label=\"Sample 2\")\n",
    "plt.bar(x3, counts[2], width=0.5, color=\"#cc3300\", label=\"Sample 3\")\n",
    "plt.legend()\n",
    "plt.axis([1, 14.0, 0, 0.5])\n",
    "# 在上面写你的代码#\n",
    "plt.savefig('figs/ex4.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,7))\n",
    "x1 = [0.1, 0.2, 0.3, 0.4, 0.5]\n",
    "y1 = [10, 15, 10, 15, 17]\n",
    "err1 = (2, 3, 4, 1, 2)\n",
    "width = 0.05\n",
    "plt.bar(x1, y1, width, color='g', yerr=err1, ecolor=\"black\")\n",
    "plt.errorbar(x1, y1, err1, fmt='ko')\n",
    "plt.title('Error bar')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 箱线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAsUAAAGfCAYAAAC3Nq8UAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAE1VJREFUeJzt3X+s5fld1/HX25lZFigbqDukLvOLBsteHI2Yu43aRTstENQCf9SEboIWvMkIiZNuIiD1qrWJk4gYXVKNyYQpCaFeghSRIIItzprcaOvegSK7TBt+ZOeHFXob0pRItp1dPv6xl013O7N3uud7z/fOfT8eySR7zznz+b6TzXfmOd/zOd9TY4wAAEBnf2LuAQAAYG6iGACA9kQxAADtiWIAANoTxQAAtCeKAQBoTxQDANCeKAYAoD1RDABAe4fnOOj9998/Tp06NcehAQBo5PLly58cYxzd7XWzRPGpU6eytbU1x6EBAGikqq7eyetsnwAAoD1RDABAe6IYAID2RDEAAO2JYgAA2hPFAAC0J4oBAGhPFAMA0J4oBgCgPVEMAEB7ohgAgPZEMQAA7YliAADaE8UA+9zGxkZOnz6dQ4cO5fTp09nY2Jh7JIAD5/DcAwBwexsbG1lfX8/Fixfz8MMPZ3NzM2tra0mSRx55ZObpAA6OGmMs/aCrq6tja2tr6ccFuNucPn0673nPe3LmzJkXHrt06VLOnTuXJ598csbJAO4OVXV5jLG66+tEMcD+dejQoTzzzDM5cuTIC4/dvHkz9957b5577rkZJwO4O9xpFNtTDLCPraysZHNz80WPbW5uZmVlZaaJAA6mSaK4qr68qn66qj5aVVeq6i9NsS5Ad+vr61lbW8ulS5dy8+bNXLp0KWtra1lfX597NIADZaoP2v1Ikl8cY/zNqronyZdMtC5Aa3/8Ybpz587lypUrWVlZyfnz533IDmBiC+8prqr7kvxakteOO1zMnmIAAJZhmXuKX5tkO8mPVdWvVtWPVtWXTrAuAAAsxRRRfDjJX0jy78YYX5/k/yX5wZe+qKrOVtVWVW1tb29PcFgAAJjGFFF8I8mNMcaHd37+6TwfyS8yxrgwxlgdY6wePXp0gsMCAMA0Fo7iMcbvJrleVV+789Cbk/zGousCAMCyTHX3iXNJ3rdz54nfSfLdE60LAAB7bpIoHmN8JMmun+oDAID9yDfaAQDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxQAAtCeKAQBoTxQDANCeKAYAoL1JvuYZAGA/qqq5R3jBGGPuEXgZohgAOLCmCNGqErQN2D4BAEB7ohgAgPZEMQAA7YliAADaE8UAALQnigEAaE8UAwDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxQAAtCeKAQBoTxQDANCeKAYAoD1RDABAe6IYAID2RDEAAO0dnnsAgA6qau4RkiRjjLlHANiXRDHAEkwRo1UlagH2iO0TAAC0J4oBAGhPFAMA0J4oBgCgPVEMAEB7ohgAgPZEMQAA7YliAADaE8UAALQnigEAaG+yKK6qQ1X1q1X181OtCQAAyzDlleJ3JLky4XoAALAUk0RxVR1L8jeS/OgU6wEAwDJNdaX4sSQ/kOSPJloPAACWZuEorqq3JPnEGOPyLq87W1VbVbW1vb296GEBAGAyU1wpfkOSb6uqp5P8ZJI3VdVPvPRFY4wLY4zVMcbq0aNHJzgsAABMY+EoHmO8c4xxbIxxKsnbkvy3McZ3LjwZAAAsifsUAwDQ3uEpFxtjPJ7k8SnXBACAveZKMQAA7YliAADaE8UAALQnigEAaE8UAwDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxdyxjY2NnD59OocOHcrp06ezsbEx90gAAJM4PPcA3B02Njayvr6eixcv5uGHH87m5mbW1taSJI888sjM0wEALMaVYu7I+fPnc/HixZw5cyZHjhzJmTNncvHixZw/f37u0QAAFlZjjKUfdHV1dWxtbS39uLxyhw4dyjPPPJMjR4688NjNmzdz77335rnnnptxMuijqjLHn9nQnXPv7lZVl8cYq7u9zpVi7sjKyko2Nzdf9Njm5mZWVlZmmggAYDqimDuyvr6etbW1XLp0KTdv3sylS5eytraW9fX1uUcDAFiYD9pxR/74w3Tnzp3LlStXsrKykvPnz/uQHQBwINhTDHCXsK8R5uHcu7vZUwwAAHdIFAMA0J4oBgCgPVEMAEB7ohgAgPZEMQAA7YliAADaE8UAALQnigEAaE8UAwDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxQAAtCeKAQBoTxQDANCeKAYAoD1RDABAe4fnHoDlqqq5R0iSjDHmHgEA4AWiuJkpYrSqRC0AcKDYPgEAQHuiGACA9kQxAADtiWIAANpbOIqr6nhVXaqqK1X1VFW9Y4rBAABgWaa4+8SzSf7+GONXqurLklyuqg+MMX5jgrUBAGDPLXyleIzxf8cYv7Lz33+Q5EqSr1p0XQAAWJZJ9xRX1akkX5/kw7d47mxVbVXV1vb29pSHBQCAhUwWxVX1qiTvT/LoGOPTL31+jHFhjLE6xlg9evToVIcFAICFTRLFVXUkzwfx+8YYPzPFmgAAsCxT3H2iklxMcmWM8a8WHwkAAJZriivFb0jyt5K8qao+svPrr0+wLgAALMXCt2QbY2wmqQlmAQB4wfFTx3Pj6o25x0iSPP/G+HyOnTyW609fn3WGg26K+xQDAEzuxtUbeez3H5t7jH3h0Vc/OvcIB56veQYAoD1RDABAe6IYAID2RDEAAO2JYgAA2hPFAAC0J4oBAGhPFAMA0J4v7wDYxYmTJ3P92rW5x0gy/7dqHT9xIteuXp11BoC9IIoBdnH92rW8/6Mfn3uMfeGtDz4w9wgAe8L2CQAA2hPFAAC0J4oBAGhPFAMA0J4oBgCgPVEMAEB7ohgAgPZEMQAA7YliAADaE8UAALQnigEAaE8UAwDQ3uG5B+DOnTpxMlevX5t7jCRJVc16/JPHT+Tpa1dnnQEAODhE8V3k6vVrGY8/MfcY+0K98aG5RwAADhDbJwAAaE8UAwDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxQAAtOfLOwCAfWm8677kR/7J3GPsC+94131zj3DgiWIAYF+qd386j/3+Y3OPsS88+upHM/7p3FMcbLZPAADQnigGAKA9UQwAQHuiGACA9kQxAADtufvEXWS8677k0pvnHmNfGG5NwxKNd92XbDw49xj7gnMPOKhE8V2k3v3pjMefmHuMfaHe+JBb07A09e5P5/0f/fjcY+wLb33wAececCDZPgEAQHuTRHFVfUtVfayqfquqfnCKNQEAYFkWjuKqOpTk3yb5a0m+LskjVfV1i64LAADLMsWV4tcn+a0xxu+MMT6b5CeTfPsE6wIAwFJMEcVfleT65/x8Y+exF6mqs1W1VVVb29vbExwWAACmMUUU1y0eG5/3wBgXxhirY4zVo0ePTnBYAACYxhRRfCPJ8c/5+VgS9y4CAOCuMUUUP5HkT1fVV1fVPUneluTnJlgXAACWYuEv7xhjPFtVfy/JLyU5lOS9Y4ynFp4MAACWZJJvtBtj/EKSX5hiLQAAWDbfaAcAQHuiGACA9kQxAADtiWIAANoTxQAAtCeKAQBoTxQDANCeKAYAoD1RDABAe6IYAID2JvmaZ5bj5PETqTc+NPcY+8LJ4yfmHgEAOEBE8V3k6WtX5x4hSVJVGWPMPQYAwGRsnwAAoD1RDABAe6IYAID2RDEAAO2JYgAA2hPFAAC0J4oBAGhPFAMA0J4oBgCgPVEMAEB7ohgAgPZEMQAA7YliAADaE8UAALQnigEAaE8UAwDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxQAAtCeKAQBoTxQDANCeKAYAoD1RDABAe6IYAID2Ds89AMB+d/zEibz1wQfmHmNfOH7ixNwjAOwJUQywi2tXr849QpKkqjLGmHsMgAPJ9gkAANoTxQAAtLfQ9omq+uEk35rks0l+O8l3jzE+NcVgAEBvx04ey6OvfnTuMfaFYyePzT3CgbfonuIPJHnnGOPZqvqhJO9M8g8WHwsA6O7609fnHiGJ/fxdLLR9YozxX8cYz+78+KEk/hkDAMBdZ8o9xX8nyX+53ZNVdbaqtqpqa3t7e8LDAgDAYnbdPlFVH0zymls8tT7G+E87r1lP8myS991unTHGhSQXkmR1ddV7EAAA7Bu7RvEY4xtf7vmqenuStyR587DhBgCAu9Cid5/4ljz/wbq/Osb4w2lGAgCA5Vr07hP/JskXJflAVSXJh8YY37PwVOyZnf9Ps6/jTQUAYD9ZKIrHGF8z1SAshxgFAPh8vtEOAID2RDEAAO2JYgAA2hPFAAC0J4oBAGhPFAMA0J4oBgCgPVEMAEB7ohgAgPZEMQAA7YliAADaE8UAALQnigEAaE8UAwDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxQAAtCeKAQBoTxQDANCeKAYAoD1RDABAe6IYAID2RDEAAO2JYgAA2hPFAAC0J4oBAGhPFAMA0J4oBgCgPVEMAEB7ohgAgPZEMQAA7YliAADaE8UAALQnigEAaE8UAwDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANqbJIqr6vuqalTV/VOsBwAAy7RwFFfV8STflOTa4uMAAMDyTXGl+F8n+YEkY4K1AABg6RaK4qr6tiT/Z4zxaxPNAwAAS3d4txdU1QeTvOYWT60n+YdJvvlODlRVZ5OcTZITJ058ASMCAMDeqjFe2a6HqvqzSX45yR/uPHQsyceTvH6M8bsv93tXV1fH1tbWKzouQFdVlVf6Zzbwyjn37m5VdXmMsbrb63a9Unw7Y4xfT/KVn3PAp5OsjjE++UrXBACAObhPMQAA7b3iK8UvNcY4NdVaAACwTK4UAwDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxQAAtCeKAQBoTxQDANCeKAYAoD1RDABAe6IYAID2RDEAAO2JYgAA2hPFAAC0J4oBAGhPFAMA0J4oBgCgPVEMAEB7ohgAgPZEMQAA7YliAADaE8UAALQnigEAaE8UAwDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxQAAtCeKAQBoTxQDANCeKAYAoD1RDABAe6IYAID2RDEAAO2JYgAA2hPFAAC0J4oBAGhPFAMA0J4oBgCgPVEMAEB7C0dxVZ2rqo9V1VNV9S+mGAoAAJbp8CK/uarOJPn2JH9ujPGZqvrKacYCAIDlWfRK8fcm+edjjM8kyRjjE4uPBAAAy7VoFL8uyTdU1Yer6r9X1UNTDAUAAMu06/aJqvpgktfc4qn1nd//FUn+YpKHkvxUVb12jDFusc7ZJGeT5MSJE4vMDAAAk9o1iscY33i756rqe5P8zE4E/6+q+qMk9yfZvsU6F5JcSJLV1dXPi2YAAJjLotsnfjbJm5Kkql6X5J4kn1x0KAAAWKaF7j6R5L1J3ltVTyb5bJK332rrBAAA7GcLRfEY47NJvnOiWQAAYBa+0Q4AgPZEMQAA7YliAADaE8UAALQnigEAaG/RW7IBcAeqal+s466ZALcmigGWQIwC7G+2TwAA0J4oBgCgPVEMAEB7ohgAgPZEMQAA7YliAADaE8UAALQnigEAaE8UAwDQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxQAAtHd47gEAAPZKVe2bdcYYE0zCXhHFAMCBJUS5U7ZPAADQnigGAKA9UQwAQHuiGACA9kQxAADtiWIAANoTxQAAtCeKAQBoTxQDANCeKAYAoD1RDABAe6IYAID2RDEAAO2JYgAA2hPFAAC0V2OM5R+0ajvJ1aUfmKncn+STcw8BDTn3YB7OvbvbyTHG0d1eNEsUc3erqq0xxurcc0A3zj2Yh3OvB9snAABoTxQDANCeKOaVuDD3ANCUcw/m4dxrwJ5iAADac6UYAID2RDFfsKr6xar6VFX9/NyzQBdV9eer6n9W1VNV9b+r6jvmngk6qKqTVXW5qj6yc/59z9wzsTdsn+ALVlVvTvIlSf7uGOMtc88DHVTV65KMMcZvVtUDSS4nWRljfGrm0eBAq6p78nwvfaaqXpXkySR/eYzx8ZlHY2KuFHNbVfXQzhWpe6vqS3f+hXx6jPHLSf5g7vngoLrVuZfknjHGbybJzl/Gn0iy683ogTt3m3PvdWOMz+y85IuinQ6sw3MPwP41xniiqn4uyT9L8sVJfmKM8eTMY8GBt9u5V1WvT3JPkt+eaUQ4kG537lXV8ST/OcnXJPl+V4kPJtsneFk7bxs9keSZPP920XM7j78xyffZPgF742XOvT+V5PEkbx9jfGi+CeFgut25t/PcA0l+Nsm3jjF+b6YR2SPeAmA3r07yqiRfluTemWeBTj7v3Kuq+/L81ap/JIhhz9z2772dK8RPJfmGGeZij4lidnMhyT9O8r4kPzTzLNDJi869natX/zHJj48x/sOsk8HB9tJz71hVfXGSVNVXJHlDko/NOB97xJ5ibquq/naSZ8cY/76qDiX5H1X1piTvTvJgkldV1Y0ka2OMX5pzVjhIbnXuJXlbkr+S5E9W1XftvPS7xhgfmWlMOHBuc+79mSQ/XFUjSSX5l2OMX59zTvaGPcUAALRn+wQAAO2JYgAA2hPFAAC0J4oBAGhPFAMA0J4oBgCgPVEMAEB7ohgAgPb+P4u7q6eWm45jAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Random test data\n",
    "np.random.seed(2018)\n",
    "all_data = [np.random.normal(0, std, size=100) for std in range(1, 4)]\n",
    "labels = ['x1', 'x2', 'x3']\n",
    "plt.figure(figsize=(12,7))\n",
    "bplot1=plt.boxplot(all_data,\n",
    "                         vert=True,  # vertical box alignment\n",
    "                         patch_artist=True,  # fill with color\n",
    "                         labels=labels)  # will be used to label x-ticks\n",
    "colors = ['pink', 'lightblue', 'lightgreen']\n",
    "for patch, color in zip(bplot1['boxes'], colors):\n",
    "    patch.set_facecolor(color)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Random test data\n",
    "np.random.seed(2018)\n",
    "all_data = [np.random.normal(0, std, size=100) for std in range(1, 4)]\n",
    "labels = ['x1', 'x2', 'x3']\n",
    "\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(15, 7))\n",
    "\n",
    "# rectangular box plot\n",
    "bplot1 = axes[0].boxplot(all_data,\n",
    "                         vert=True,  # vertical box alignment\n",
    "                         patch_artist=True,  # fill with color\n",
    "                         labels=labels)  # will be used to label x-ticks\n",
    "axes[0].set_title('Rectangular box plot')\n",
    "colors = ['pink', 'lightblue', 'lightgreen']\n",
    "for patch, color in zip(bplot1['boxes'], colors):\n",
    "    patch.set_facecolor(color)\n",
    "\n",
    "# notch shape box plot\n",
    "x1 = [0.1, 0.2, 0.3, 0.4, 0.5]\n",
    "y1 = [10, 15, 10, 15, 17]\n",
    "err1 = (2, 3, 4, 1, 2)\n",
    "\n",
    "width = 0.05\n",
    "axes[1].bar(x1, y1, width, color='g', yerr=err1, ecolor=\"black\")\n",
    "axes[1].errorbar(x1, y1, err1, fmt='ko')\n",
    "axes[1].set_title('Error bar')\n",
    "axes[1].set_xticklabels([\"\", \"x1\", \"\", \"x2\", \"\", \"x3\", \"\", \"Tree4\"])\n",
    "\n",
    "# adding horizontal grid lines\n",
    "for ax in axes:\n",
    "    ax.yaxis.grid(True)\n",
    "    ax.set_xlabel('samples')\n",
    "    ax.set_ylabel('values')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 驱动器 C 中的卷没有标签。\n",
      " 卷的序列号是 5E1B-A9CE\n",
      "\n",
      " C:\\Users\\admin\\Desktop\\Class11 的目录\n",
      "\n",
      "2020/12/18  10:47    <DIR>          .\n",
      "2020/12/18  10:47    <DIR>          ..\n",
      "2019/11/28  19:50             8,196 .DS_Store\n",
      "2020/12/18  08:00    <DIR>          .ipynb_checkpoints\n",
      "2020/12/18  08:00    <DIR>          csv\n",
      "2020/12/18  08:00    <DIR>          figs\n",
      "2020/12/18  08:00    <DIR>          files\n",
      "2020/12/18  10:47           733,700 matplotlab动画.ipynb\n",
      "2020/12/18  10:43           513,979 matplotlib基础绘图2.ipynb\n",
      "2020/12/08  23:28            20,693 numpy入门.ipynb\n",
      "2019/11/27  22:37            17,395 热身练习.ipynb\n",
      "2020/12/14  19:19           595,172 直方图，箱线图和正态分布.pptx\n",
      "               6 个文件      1,889,135 字节\n",
      "               6 个目录 34,803,904,512 可用字节\n"
     ]
    }
   ],
   "source": [
    "!dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 648x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习5\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "all_data = [[], [], [], []]\n",
    "labels = [\"Tree1\", \"Tree2\", \"Tree3\", \"Tree4\"]\n",
    "for i in range(1,5):\n",
    "    input_file = open(\"./files/tree_\"+str(i)+\".txt\")\n",
    "    all_data[i-1] = list(map(float, [i for i in input_file]))\n",
    "    input_file.close()\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(15, 7))\n",
    "\n",
    "# 在下面写你的代码#\n",
    "\n",
    "# 在上面写你的代码#\n",
    "\n",
    "# adding horizontal grid lines\n",
    "for ax in axes:\n",
    "    ax.yaxis.grid(True)\n",
    "    ax.set_xlabel('Samples')\n",
    "    ax.set_ylabel('Height')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习5-答案\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "all_data = [[], [], [], []]\n",
    "labels = [\"Tree1\", \"Tree2\", \"Tree3\", \"Tree4\"]\n",
    "for i in range(1,5):\n",
    "    input_file = open(\"./files/tree_\"+str(i)+\".txt\")\n",
    "    all_data[i-1] = list(map(float, [i for i in input_file]))\n",
    "    input_file.close()\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(15, 7))\n",
    "\n",
    "# 在下面写你的代码#\n",
    "bplot1 = axes[0].boxplot(all_data,\n",
    "                         vert=True,  # vertical box alignment\n",
    "                         patch_artist=True,  # fill with color\n",
    "                         labels=labels)  # will be used to label x-ticks\n",
    "axes[0].set_title('Four trees\\' height')\n",
    "colors = ['pink', 'lightblue', 'lightgreen', 'lightgray']\n",
    "for patch, color in zip(bplot1['boxes'], colors):\n",
    "    patch.set_facecolor(color)\n",
    "\n",
    "\n",
    "x1 = [1, 2, 3, 4]\n",
    "y1 = [np.mean(all_data[0]), np.mean(all_data[1]),\n",
    "      np.mean(all_data[2]), np.mean(all_data[3])]\n",
    "err1 = [np.std(all_data[0], ddof=1), np.std(all_data[1], ddof=1),\n",
    "        np.std(all_data[2], ddof=1), np.std(all_data[3], ddof=1)]\n",
    "\n",
    "width = 0.5\n",
    "axes[1].bar(x1, y1, width, color='g', yerr=err1, ecolor=\"black\")\n",
    "axes[1].errorbar(x1, y1, err1, fmt='ko')\n",
    "\n",
    "axes[1].set_title('Four trees\\' height')\n",
    "axes[1].set_xticklabels([\"\", \"Tree1\", \"\", \"Tree2\", \"\", \"Tree3\", \"\", \"Tree4\"])\n",
    "\n",
    "# 在上面写你的代码#\n",
    "\n",
    "# adding horizontal grid lines\n",
    "for ax in axes:\n",
    "    ax.yaxis.grid(True)\n",
    "    ax.set_xlabel('Samples')\n",
    "    ax.set_ylabel('Height')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 热图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "from matplotlib import cm\n",
    "import csv\n",
    "\n",
    "\n",
    "def draw_heatmap(data, xlabels, ylabels):\n",
    "    cmap = cm.Blues\n",
    "    figure = plt.figure(facecolor='w')\n",
    "    # ax = figure.add_subplot(3, 4, 9) 将画布分割成3行4列，图像画在从左到右从上到下的第9块\n",
    "    ax = figure.add_subplot(1, 1, 1)\n",
    "    ax.set_yticks(range(len(ylabels)))\n",
    "    ax.set_yticklabels(ylabels)\n",
    "    ax.set_xticks(range(len(xlabels)))\n",
    "    ax.set_xticklabels(xlabels)\n",
    "    vmax = data[0][0]\n",
    "    vmin = data[0][0]\n",
    "    for i in data:\n",
    "        for j in i:\n",
    "            if j > vmax:\n",
    "                vmax = j\n",
    "            if j < vmin:\n",
    "                vmin = j\n",
    "    my_map = ax.imshow(data, interpolation='nearest', cmap=cmap, aspect='auto', vmin=vmin, vmax=vmax)\n",
    "    plt.colorbar(mappable=my_map, cax=None, ax=None, shrink=0.5)\n",
    "    plt.xticks(rotation=90)  # 将字体进行旋转\n",
    "    plt.yticks(rotation=360)\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "with open(r'.\\csv\\ka.csv','r', newline='') as csv_file_r:\n",
    "    csv_reader = csv.reader(csv_file_r, delimiter=',', quotechar='\"')\n",
    "    x_labels = next(csv_reader)[1:]\n",
    "    x_labels = list(map(lambda x: float(x.replace('X','')), x_labels))\n",
    "    y_data = []\n",
    "    y_labels = []\n",
    "    for row in csv_reader:\n",
    "        y_data.append(list(map(float, row[1:])))\n",
    "        y_labels.append(row[0])\n",
    "    csv_file_r.close()\n",
    "    draw_heatmap(y_data, x_labels, y_labels)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 练习6\n",
    "import csv\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "def heatmap(data, row_labels, col_labels, ax=None,\n",
    "            cbar_kw={}, cbarlabel=\"\", vmin=-10, vmax=10, **kwargs):\n",
    "    # Plot the heatmap\n",
    "    im = ax.imshow(data, **kwargs, interpolation='nearest', aspect='auto', vmin=vmin, vmax=vmax)\n",
    "    # Create colorbar\n",
    "    cbar = ax.figure.colorbar(im, ax=ax, **cbar_kw)\n",
    "    cbar.ax.set_ylabel(cbarlabel, rotation=-90, va=\"bottom\")\n",
    "\n",
    "    # We want to show all ticks...\n",
    "    ax.set_xticks(np.arange(data.shape[1]))\n",
    "    ax.set_yticks(np.arange(data.shape[0]))\n",
    "    # ... and label them with the respective list entries.\n",
    "    ax.set_xticklabels(col_labels)\n",
    "    ax.set_yticklabels(row_labels)\n",
    "\n",
    "    # Let the horizontal axes labeling appear on top.\n",
    "    ax.tick_params(top=True, bottom=False,\n",
    "                   labeltop=True, labelbottom=False)\n",
    "\n",
    "    # Rotate the tick labels and set their alignment.\n",
    "    plt.setp(ax.get_xticklabels(), rotation=-30, ha=\"right\",\n",
    "             rotation_mode=\"anchor\")\n",
    "\n",
    "    # Turn spines off and create white grid.\n",
    "    for edge, spine in ax.spines.items():\n",
    "        spine.set_visible(False)\n",
    "    ax.set_xticks(np.arange(data.shape[1]+1)-.5, minor=True)\n",
    "    ax.set_yticks(np.arange(data.shape[0]+1)-.5, minor=True)\n",
    "    ax.grid(which=\"minor\", color=\"w\", linestyle='-', linewidth=3)\n",
    "    ax.tick_params(which=\"minor\", bottom=False, left=False)\n",
    "\n",
    "    return im, cbar\n",
    "\n",
    "# 看懂并改造这个文件\n",
    "# 让这个热图变得美观\n",
    "# 试试看能否自定义是否显示热图中的文字\n",
    "\n",
    "# 数据位置\n",
    "value_result = r\".\\csv\\value.csv\"\n",
    "# 第几列是数据\n",
    "x_index = 2\n",
    "# 第几列是Y坐标轴标题\n",
    "label_index = 0\n",
    "# 色轴最大值和最小值\n",
    "v_min, v_max = -15, 15\n",
    "# 配色方案\n",
    "cmcolor = 'rainbow'\n",
    "\n",
    "y_data = []\n",
    "x_data = []\n",
    "y_labels = []\n",
    "with open(value_result, 'r', newline='') as csv_file_r:\n",
    "    csv_reader = csv.reader(csv_file_r, delimiter=',', quotechar='\"')\n",
    "    x_data = list(map(lambda x: x.split(\"_\")[0], next(csv_reader)[x_index:]))\n",
    "    for row in csv_reader:\n",
    "        y_data.append(list(map(lambda x: round(float(x), 2) if x != \"\" else 0, row[x_index:])))\n",
    "        y_labels.append(row[label_index])\n",
    "        main_data = np.array(y_data)\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# We want to show all ticks...\n",
    "ax.set_xticks(np.arange(len(x_data)))\n",
    "ax.set_yticks(np.arange(len(y_labels)))\n",
    "# ... and label them with the respective list entries\n",
    "ax.set_xticklabels(x_data)\n",
    "ax.set_yticklabels(y_labels)\n",
    "\n",
    "# Rotate the tick labels and set their alignment.\n",
    "plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n",
    "         rotation_mode=\"anchor\")\n",
    "# Loop over data dimensions and create text annotations.\n",
    "for i in range(len(y_labels)):\n",
    "    for j in range(len(x_data)):\n",
    "        text = ax.text(j, i, main_data[i, j],\n",
    "                       ha=\"center\", va=\"center\", color=\"k\")\n",
    "\n",
    "im, cbar = heatmap(main_data, y_labels, x_data, ax=ax, vmin=v_min, vmax=v_max,\n",
    "                   cmap=cmcolor, cbarlabel=\"\")\n",
    "fig.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "import csv\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "def heatmap(data, row_labels, col_labels, ax=None,\n",
    "            cbar_kw={}, cbarlabel=\"\", vmin=-10, vmax=10, **kwargs):\n",
    "    # Plot the heatmap\n",
    "    im = ax.imshow(data, **kwargs, interpolation='nearest', aspect='auto', vmin=vmin, vmax=vmax)\n",
    "    # Create colorbar\n",
    "    cbar = ax.figure.colorbar(im, ax=ax, **cbar_kw)\n",
    "    cbar.ax.set_ylabel(cbarlabel, rotation=-90, va=\"bottom\")\n",
    "\n",
    "    # We want to show all ticks...\n",
    "    ax.set_xticks(np.arange(data.shape[1]))\n",
    "    ax.set_yticks(np.arange(data.shape[0]))\n",
    "    # ... and label them with the respective list entries.\n",
    "    ax.set_xticklabels(col_labels)\n",
    "    ax.set_yticklabels(row_labels)\n",
    "\n",
    "    # Let the horizontal axes labeling appear on top.\n",
    "    ax.tick_params(top=True, bottom=False,\n",
    "                   labeltop=True, labelbottom=False)\n",
    "\n",
    "    # Rotate the tick labels and set their alignment.\n",
    "    plt.setp(ax.get_xticklabels(), rotation=-30, ha=\"right\",\n",
    "             rotation_mode=\"anchor\")\n",
    "\n",
    "    # Turn spines off and create white grid.\n",
    "    for edge, spine in ax.spines.items():\n",
    "        spine.set_visible(False)\n",
    "    ax.set_xticks(np.arange(data.shape[1]+1)-.5, minor=True)\n",
    "    ax.set_yticks(np.arange(data.shape[0]+1)-.5, minor=True)\n",
    "    ax.grid(which=\"minor\", color=\"w\", linestyle='-', linewidth=3)\n",
    "    ax.tick_params(which=\"minor\", bottom=False, left=False)\n",
    "\n",
    "    return im, cbar\n",
    "\n",
    "\n",
    "# 看懂并改造这个文件\n",
    "# 使之能够能够自定义是否显示热图中的文字\n",
    "# 使之能够用命令行的形式生成热图\n",
    "if __name__ == \"__main__\":\n",
    "    # 数据位置\n",
    "    value_result = r\".\\csv\\value.csv\"\n",
    "    # 第几列是数据\n",
    "    x_index = 2\n",
    "    # 第几列是Y坐标轴标题\n",
    "    label_index = 0\n",
    "    # 色轴最大值和最小值\n",
    "    v_min, v_max = -15, 15\n",
    "    # 配色方案\n",
    "    cmcolor = 'autumn'\n",
    "\n",
    "    csv_file_r = open(value_result, 'r', newline='')\n",
    "    csv_reader = csv.reader(csv_file_r, delimiter=',', quotechar='\"')\n",
    "    x_data = list(map(lambda x: x.split(\"_\")[0], next(csv_reader)[x_index:]))\n",
    "    y_data = []\n",
    "    y_labels = []\n",
    "    for row in csv_reader:\n",
    "        y_data.append(list(map(lambda x: round(float(x), 2) if x != \"\" else 0, row[x_index:])))\n",
    "        y_labels.append(row[label_index])\n",
    "    csv_file_r.close()\n",
    "\n",
    "    main_data = np.array(y_data)\n",
    "    fig, ax = plt.subplots(figsize = (12,7))\n",
    "\n",
    "    # We want to show all ticks...\n",
    "    ax.set_xticks(np.arange(len(x_data)))\n",
    "    ax.set_yticks(np.arange(len(y_labels)))\n",
    "    # ... and label them with the respective list entries\n",
    "    ax.set_xticklabels(x_data)\n",
    "    ax.set_yticklabels(y_labels)\n",
    "\n",
    "    # Rotate the tick labels and set their alignment.\n",
    "    plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n",
    "             rotation_mode=\"anchor\")\n",
    "    # Loop over data dimensions and create text annotations.\n",
    "    for i in range(len(y_labels)):\n",
    "        for j in range(len(x_data)):\n",
    "            text = ax.text(j, i, main_data[i, j],\n",
    "                           ha=\"center\", va=\"center\", color=\"k\")\n",
    "\n",
    "    im, cbar = heatmap(main_data, y_labels, x_data, ax=ax, vmin=v_min, vmax=v_max,\n",
    "                       cmap=cmcolor, cbarlabel=\"\")\n",
    "    fig.tight_layout()\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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+qAzlc71Mz52R88ynb2P28pSRuDx2NbaTXozmMbvjNGYe77ZXxuhUMlMry5rcK88Nrkdz/SzU3fkrWa6zecuZpnt9ypmpB9acZameq/yqrvmh7tZ3y3P9cvn5QFv2qJr6LCbmVjSMsSK1l/vmdSuy2MGxYm5FTVtW1hZZ+xa9uCg9L2K2GOjTj83r79CrkwbblNWrpn6u19b9t64or9CL2pdtW9IPx4h5dMq7dL6kLZdiXWZmZjZdpnpDExGPHCPsRcB7ImJNRGwYFazCVB+3mZmZzc9U/8Mu6Yb0uL+kU1LG7W4Gbkl6BfBc4J8lHZtiD5F0Vsq0fXiqWy3pcknHAOuA+0m6QdK7JF2QMnDfsxR7cup/kqT7L8/Rm5mZ2bimekOTeSjwRopkkQ8EHhURn6TImn1IRLxI0gHADhQfrLcG2EvSfqn/DsC/R8QuEXENsDXwo4jYAzgVeGWK+zDwmZTL6VjgyKU5PDMzM1uoNm1ofhIRv0jZsc+nnx277ID0dR5wLrATxUYG4JqI+FEp9hbg+PT8nNJ4jwA+n55/lmqGbzMzM5sybforp3J27E3Ur10U99N8fKBSWk2RdLLs1uh/CE/TeGZmZtYCbTpDM44TgJeljNtIuo+k7eY5xg+B56fnLwJOm+D6zMzMbBHM1FmJiPiepIcAZ6bPHbkBeDHFGZhxvQH4tKRDgN8AfzXxhZqZmdlETfWGJiJWpcdTgFNK9a8vPT8o63MEcETNcLtmcatKz78KfDU9vwZ43Oau3czMzJbOrF1yMjMzs9shb2jMzMys9Zxt28zMzFrPZ2jMzMys9ab6puBpN69s2w1lMZiNtciY3ZBdO8uyXanXXE2fpmzb1fbmLN7VzNz5fHXZuwfL1fpqRu4VWWzKih35GHOl7NqDsfljXSZvjczQnep7yXY18LyIJcXkWb0ZbEfNmbKbsn6XkvxqROywbN/N89bXz69PNZN3U5Lifjl6sdW+9RnA+7FNfaMxZli27+bjyOcZzIo9kBm8KaahfiAD+ojs4vVZvgePpy7zeG39XJT60Kur7TvXL1czYndjsnVkCaWZi0oslZjuGN2y+u2V2MFvqBrepCq/CbM3rvI3Rbldecy4j3OVHzyV24b11dzgOE3j53265cYs33lsvz4qWbybYwfLc0Niu9m8h4zZlIF8nDEbspVvsWL/9mXbNjMzMxuHNzRmZmbWelO5oUkZry+TtFbSFSm79p9JOkPSlZL2SV9nSjpP0g8lPTj13UrSlyVdIunrkn4sae/UdoOkD0i6WNL30xinSPqppKeX5j5N0rnp65HL+VqYmZnZaFO5oUkeBHyQIsHkTsALKRJFHgy8BbgMeHREPBR4O/Du1O+1wO8iYmfgH4G9SmNuDZwcEbsAfwDeCTwBOBB4R4r5NfCEiNgTeB7Otm1mZjb1pvmm4Ksj4iIASRcDJ0VESLqIIjP2XYDPSNoBCOAOqd++pE8Kjoh1ki4sjXkL8N30/CLg5oi4tTQmaZyPSFpDkTJhx0U6PjMzM5uQaT5DU86u3SmVOxQbsX8GfhARuwJPA1aOMWY5w3ZvzIjojgnwJuBaYA9gb+COm3EMZmZmtgSmeUMzyl2AX6bnB5XqzwCeCyBpZ2C3BYz7X2mT85eQ/pbYzMzMplabNzTvB94j6TwGL539O3APSZdQ3CNzMXD9PMb9d+Clki6guHfnxgmt18zMzBbJVN5DExHrKWXHLmfUztrK97e8LT1uBF4cERslbQ98H7gm9S1n2D4sm7Ob2ftKYPdS05s351jMzMxs8U3lhmYzbQX8QNIdKD5L8rURccsyr8nMzMwW0cxtaCLiDxQ385qZmdnthLNtm5mZWeu1+aZgMzMzM2AGLzktsQDIz3KVy8PaNrfvUs9XV26KyR/r2kf1HWfMSfSZRN9hj+OOPw1987pOpzO0T7l9nJim9lFrGzbGqPHns9Zx5l3Ie2Dc45zk92Zz17w535NJHudC+jatLa+v+57UxTSNtZA+3fJ81pjHjTvfpN4/84nNx16k99FsZduWdE9Jn095mM5JeZ0OXO51mZmZ2dJr5YZGkoBvAKdGxAMjYi/g+cB9szifgTIzM7sdaOWGBngccEtEfKxbERHXRMSHJR0k6ThJJwMnAUg6RNJZki6UdHiqe4ekN3b7S3qXpL+VdC9Jp0o6X9I6SY9e6oMzMzOz+WnrGYxdgHOHtO8J7B4R10k6ANgB2Ific2mOk7Qf8Cnga8CHJM1RnOHZhyKNwgkR8S5JKyg+18bMzMymWFs3NAMkHUWRZfsW4CjgxIi4LjUfkL7OS+VVwA4Rcaqk30p6KHBP4LyI+K2ks4BPpQ/m+0ZEnL+kB2NmZmbz1tYNzcXAs7qFiHidpG2Bs1NVOf+SgPdExMdrxvkkxRmZP6Y4Y0Pa6OwHPAVYK+lfI+KYyR+CmZmZTUpb76E5GVgp6TWluqZLQycAL5O0CkDSfSRtl9q+DjwJeFiKQ9KfANdGxCcoNjx7LsL6zczMbIJaeYYmIkLSM4F/k3Qo8BuKszJvBrbMYr8n6SHAmcUfR3ED8GLg1xFxi6QfAL+PiE2py/7AIZJuTbEvWYpjMjMzs4Vr5YYGICL+i+JG3jprs9gjgCPyoHQz8J8CzynFfgb4zMQWamZmZouurZecNpuknYH/BE6KiCuXez1mZma2cK09Q7O5IuIS4IHLvQ4zMzPbfM62bWZmZq13u73kZGZmZrPjdnvJaRI23dYJ6GcA7SqKUXpebuw+1PUZLPSqgqyc9S09iUpw3mXI2LXHUS5X2/M1RcNaY7AIETVryF6zpvqBeQYnbKwvH0NdXXZc5fqI0vN8zflx15SHtdWtY5y+I+cfc22j56vv05u/E/PuWztvZ359Gbbmzuh5R78WWT2l8tivZ7V+nO950xjln53haxwyb6f5+zcwdqe+bmDcTtZeHrOubmCs/P3crx/2Hiuvoz9HacyG90K1vj9GXjfquMvrGrXWxmOIYeOPrh973vJ8DT8XI4+z/N5bwBiV3111r0XTGJV5iodT4h3tyrYtaVMpn9JXJE0kBYGk/SUdP4mxzMzMbDpM7YYG2BARayJiV4qUBq8et6OzbJuZmd2+TPOGpuw04EGSVkta162UdLCkw9LzUyR9SNLZwN9KWivpY5LOlnSFpKfmg0raWtKnJP1E0nmSnpHqd0l156cM3Tss0XGamZnZAkz9mYx0tuXJwHfHCL9jROyd+q0FVlNk0N4e+IGkB2XxbwVOjoiXSbor8BNJ36c4G3RERBwr6Y7AiokcjJmZmS2Kad7QbCmpm+n6NOBo4N4j+nwpK385IjrAlZJ+CuyUtR8APF3Swam8Erg/cCbwVkn3Bb7mD94zMzObbtO8odkQEWvKFZJuY/Ay2cqsz41ZOUaUBTwrIi7P6i+V9GOKjNvfkfSqiDh5/KWbmZnZUmrLPTRd1wLbSbq7pDsBlftiMs+RNCdpe4pPBc43LicAb1DKWinpoenxgcBPI+JI4JvA7pM8CDMzM5usaT5DUxERt0p6B/AT4JfAZSO6/CzF3hl4dURsTHuXrn8GPgRcmBJVXk2xSXou8Jcp4/b/A9490QMxMzOziZraDU1ErGqoPxI4sqZ+/5rw70fEq7O4U4BT0vMNwKtqxnov8N75rtnMzMyWR9suOZmZmZlVTO0Zms0VEQct9xrMzMxsaTjbtpmZmbWeLzmZmZlZ683sJaelsPG2bpLqLANpqa4rSxZayZBLTd+6trq+5akaM+9mC6ltH9F3WLbtcY+3jX1LiXHpZJm/80zgde29toY+3XJde7WturaiPf/eRamtvk+33CmVs6TIlePp9B6r9b3xen2zefKxS/V5XT5/U9+IIWtqmL+81qZ5K697TebqurbymuuyXlfmaRqrZu0j19z0nqjpO17m9eExncas5gubrz/vfPswpO/gYzULdYwV09Q+n3kqjwtYaz5v/43SS1E9WO6Uyk0x45THjq2pX8h8I/puOO8j7cq2PY5SRu4LJJ0r6ZGpfiDnk5mZmc22tp+h6X2asKQnAu8BHrO8SzIzM7Ol1uozNJk7A7/LKyUdJOkjpfLxkvZPzw+QdGY6u/MVSatS/XslXZIybf/LUh2AmZmZLUzbz9B0E1iuBO4FPG7cjpK2Bd4G/FlE3CjpzcDfSToKOBDYKSIiZeE2MzOzKdb2DU35ktMjgGMk7Tpm3z8FdgbOSOkQ7kiRZft6YCNwtKTjgeMnvmozMzObqLZvaHoi4sx01uUeWVNThm4BJ0bEC/KxJO0DPB54NvB65nHmx8zMzJbezNxDI2knYAXw26xpPbAmZd2+H7BPqv8R8ChJD0r9t5a0Y7qP5i4R8R3gTcAeS3IAZmZmtmBtP0PTvYcGijMuL42ITVlG7TMosmhfAlwKnAsQEb+RdBDwBUl3SrFvA/4AfFPSyjTm3y36UZiZmdlmafWGJiJWNNSvB3ZNzwN4UUPcycDDapr2qakzMzOzKTUzl5zMzMzs9ssbGjMzM2s9Z9s2MzOz1vMZGjMzM2u9Vt8UvNw2bropoJzltn+2K/qpUlO531Ju79XPY4woPcvHKPef9xg1axhYa6U9KnVNsXVxm9M3X+tiz5u39bNbd4b27Qz0HR072N4ZMm/Tmjs189bHdlJsub0yT29t2dpr1py/JvkYw8YeNm79cffnaB53MLbue5JnKe/k9TVx48Q0jVXNAN609mpc/hrkGborY5XWUc3YTFautm9OJulxxl9o3+FZqOvbGjOTL+i16X+PFnJ8+VorPyejxij/bPe/yQOvTakzpcUOxjT2qWkvj1MX2z+Yav3IPkPmb1hbnPiL9mXblnRPSZ+X9FNJ56S8Swcu97rMzMxsukzthkbFh8l8Azg1Ih4YEXsBzwfum8X5LJOZmdnt3NRuaCjSDdwSER/rVkTENRHx4ZRB+zhJJwMnAUg6RNJZKUP24d0+kl4s6SeSzpf0cUkrUv0Nkt4l6QJJP5J0z1T/HEnrUv2pS3vIZmZmthDTvKHZhfSpvg32BJ4dEY+RdACwA8UH4q0B9pK0n6SHAM8DHpWSWG6i/yF7WwM/iog9gFOBV6b6twNPTPVPn/RBmZmZ2eS15nKNpKOAfYFbgKMoEktel5oPSF/npfIqig3O7sBewFkpHcKWwK9TzC30M2mfAzwhPT8DWCvpy8DXFut4zMzMbHKmeUNzMfCsbiEiXpeyaZ+dqm4sxQp4T0R8vDyApDcAn4mIf6gZ/9bofwjPJtJrERGvlvRw4CnAOZL2iog84aWZmZlNkWm+5HQysFLSa0p1WzXEngC8LGXKRtJ9JG1HcX/Ns9NzJP2RpD8ZNqmk7SPixxHxduA3wP0290DMzMxscU3tGZqICEnPBP5N0qEUm4sbgTdTXDoqx34v3S9zZrq0dAPw4oi4RNLbgO9JmgNuBV4HXDNk6g9I2oHirM9JwAUTPjQzMzObMKc+2Az+YD1/sJ4/WK9f9gfrjR7LH6w3ev5RfYfN39TXH6xXrhvVp6a9PE5dbP9gqvX+YD0zMzOz8XlDY2ZmZq3nS05mZmbWej5DY2ZmZq03tX/l1Ao3/XdA6Wa1gRtws5uy5l0eI7aufth4o8YcMV/tcUYnq+s0zFNTn9dVxmqq74w3fl19dMYYP+/bqa9rHD+rz+s6o/oM6TufdYw9X02f/KbCxvlrvifjxDb1bVzrkPUsYL5oGK9X3+m+56vzR8O4kR1DdY6oHa8YqmGscdbciYa+/TErN5GOuAG1+HXQ0NYh61sTF3lMPn59ffGrs6ktuzF0yLz5vanZS9S7D7V832lTn8axyjF0x9fwsXpx1XthO1ls0z2zndrxNVCuu/92offmRvk1WsAYk7gXuRdLcZyHXXbr9N4ULOm+kr4p6UpJV0k6QtIdl3tdZmZm1g7LvqFJWbW/BnwjInYAdqRIXfCuLM5nk8zMzKzWsm9oKLJqb4yITwNExCbgTRSf/PvaclZtSasknSTpXEkXSXoGgKTVki6V9AlJF0v6nqQtU9vDUgbu8yV9QNK6VL8ilbsZul+V6u8l6dQUv07So5fjRTEzM7PxTcOGZheK5JA9EfE/wM8o7vHpZdUGNgIHRsSewGOBD6YzPFAkozwqInYBfk8/D/1SRfkAACAASURBVNSngVdFP9t218uB6yPiYcDDgFdKegDwQuCEFL8HcP6kD9jMzMwmqw2XccpZtQW8W9J+FPcf3Qe4Z2q7OiK6m49zgNWS7gpsExFnpvrPA09Nzw8Adpf07FS+C8Wm6CzgU5LuQHEZzBsaMzOzKTcNG5pLgGeXKyTdGbg/cBuDWbVfBNwD2CsibpW0HliZ2m4uxW0iy/dUQ8AbIuKESkOxYXoKsFbSv0bEMeMfjpmZmS21abjkdBKwlaSXQHFvC/BBYC1wUxZ7F+DXaTPzWOBPhg0cEb8H/iDp4anq+aXmE4DXpDMxSNpR0tYpG/e1EfEJ4JMUl7zMzMxsii37hiaKDxM4EHiOpCuBKyjulXlLTfixwN6SLgJeAlw2xhQvBz4h6Xxga+D6VP9JirND56YbhT9OccZqf+ACSecBzwOOWOChmZmZ2RKZ+dQHklZFxA3p+d8D94qIv53I4P5gvf6Hd/mD9Zrr/cF64/f1B+s19PUH6/mD9fplf7Be/QfrTcM9NIvtKZL+geJYrwEOWt7lmJmZ2aTN/IYmIr4EfGm512FmZmaLZ+YvOZmZmdnsW/abgs3MzMw218xfclpUN10fUHMDX/kG26YbbYfWjxtLtX5B84235tqbEptuvBznRtTeTasNY+Q3apbjx7kZt2kdo24erVvPqLUOu5m1qa3xuEtjjt2npn3cG23LN7HWraFubXXtC+mzTH3zm3/7N+cOL9OJ/o9H0824nfoyEbXjzb8v4/UdWHMMVHXL/bdLtb32ht2BYevHLN56I+ZrvPF3cJz6vs1jVOZLL1XvN1rvJYxeffVG1qjt0x+r3169aTVbaz4//TVX1kZ2PGTzRmnerG8nO978JuROxNC2UX3ztfRjoqFPv31Y23z7dlfysfjD9GbbngRJm0r5l76VPiV4Pv0Pk3TwYq3PzMzMFs/MbGiADRGxJiJ2Ba4DXrfcCzIzM7OlMUsbmrIzKfI8ASDpkFJW7cNL9W+VdIWk04EHl+r/RtIlKf6LS7t0MzMzm6+Zu4cmpU54PHB0Kh9AkXRyH4r8TcelXE03UqRCWEPxOpxLP+v33wMPiIib53vpyszMzJbeLG1otkzpDe4DXAqcmOoPSF/npfIqig3ONsDXI+ImAEnHlca6EDhW0jeAbyzB2s3MzGwzzNIlpw0RsYYiYaXo30Mj4D3p/po1EfGgiDh6xFhPAY6iSEx5lqRZ2viZmZnNnFna0ACQzrj8DfC/0kbkBOBlklYBSLqPpO2AU4FnStpS0jbA01L7HHC/iPgB8GaKDN+rluFQzMzMbEwzeeYhIs6TdCHwgoj4rKSHAGdKArgBeHFEnCvpS8AFwK+Bs1L3FcDnJN2F4uzOkRHx+6U/CjMzMxvXzGxoImJVVn5a6fkRwBE1fd4FvKtmuH0nvkAzMzNbNDN3ycnMzMxuf7yhMTMzs9Zztm0zMzNrPZ+hMTMzs9abmZuCl8evBtPClnOg1tUBvbyheUbrcnulLRtrWHs09Kn0nc+au1lg69bRkOF4rPrN6dtLE5zFjFHfFFvJRF7K4F3J5t30uCkbcz59ax7nO9+C1lzuk2d5zjNzV1Ie9+tHxQ4bc9ws35X5O8PX1DBfPyN1N2Swbwyrr2Ti7oYMry8yZpONl/8KiaxPaR3Z2vLs2v23dXUdjdmta7Jsd8vDMmIP9q3GLaTPyHmHrDWft/Gtx2C5/NbLs253RvSNqGaKjlD9/EP61q2prm95XdW+qh+r1LcyTr6mIeX8X4Z+zODx1s2xkPma+nZjPn7FLe3Otq3C6ZKeXKp7jqTvSrqhVLeLpJMlXS7pSkn/qPT32jVj7i/p+pSl+0JJ30+fUWNmZmYt0poNTRTb8VcD/yppZfqgvHdTyqotaUvgOOC9EfFgYA/gkcBr8/FKn/57WvoE4d0pPoumkqXbnxRsZmY23Vr1D3VErJP0LYpP8N0aOCYiriqdgHkhcEZEfC/F3yTp9cApwFGSDgO2Bx4I/Az4eLdjOouzDfCfqZzHvmCRD8/MzMwWqFUbmuRwiszYtwB7Z2270M+YDUDa8KySdOdUtTOwb0RskLQ/8OiU1PLuFBm431Lq3oud/GGYmZnZpLTmklNXRNwIfAn4bETcvIAhjss2KN1LTvcDPg28f0ismZmZTaHWbWiSDv0bn8suAfYqV0h6IHBDRPxPqrpxyLjHAfuVysNizczMbEq0dUPT5FhgX0l/Br2bhI9k8KzLMPsCVy3S2szMzGyRtPEemkbpvphnAB+WdBRF5uzPAh8Z0q17D42A64FXLP5KzczMbJJauaGJiMOy8qrS84uA/cfsdwpwl3FizczMbHrN2iUnMzMzux3yhsbMzMxaz9m2zczMrPV8hsbMzMxar5U3BU+PcwZT5ZazQo/M6DwsS3SWbrWSfbop+/ak5q0ff/LZtrO2UVmvJzVvU2zTa1Tu022ry/pcLpczPedrmc8YdWsZiGlqr8tCPWSNpOzFvZdiRErcvL3cd5zYfOxxY+tSEM8nNrVH3panC85TH5frF9KnW15InwnMW8lUnWcE77aX3yKVuvpy78eoVN9P4D5qnmyMGCOm4Vjqfi1UE7EPZqUusl4ri+kuebC+k49R/rXAYNtmzduQOXvYvJ1u1uteufrY1BZD+ozqO+oxFtBn2Lzdtf5TXN7ObNtLkGX7Mkn/MmT+9ZK2nexRmZmZ2SRN/YZmsbNsAw8FnirpUYt7JGZmZrZYWnHJaTGzbKcP4zsfuA+ApLsDX0jlM4HaszxmZmY2PVqxoUkmnWUbAEl3A3YATk1V/wScHhHvkPQU4OUTPxIzMzObqNZsaCLiRklfokg0OYks24+WdAHFZuZDEfH/Uv1+wF+kOb8t6XebtXAzMzNbdFN/D01mklm2T4uIPSjO7rxc0ppJL9bMzMyWRts2NE0WnGU7Iq4G3ktxfw4Ul55emMZ5MnC3xViwmZmZTc5MbGjSpaRnAG+TdDlwEXAWw7Nsl30M2E/Saop7dfaTdDHFpaefTXzBZmZmNlGtuYcGmHSW7VNK5Q2kv3JKDtjMpZqZmdkSmokzNGZmZnb75g2NmZmZtZ6zbZuZmVnr+QyNmZmZtV6rbgqeOht/G0BDFuosheqoDNoL6VsX19gny7g8r76lbMyV9ttBtm3qMjo3vb41cePEVI6v25fRMXVjlr+flXnq54/yWvMs3llm7ko64U5NVvHKGEPGbMoMXjdPPsao7OU1Y0T2uuVZofuvCQNjFG/b7HXrNPSpZJLufz8r2b4b+g6MPWxNQ9ZDUMpIPfia9Ou75X57Xhed/LgHx4zymHV1A8fdqa2PTqd0XFnf7Huf10eRwrp23E7TmBE1a0h9amKXpy8j+47KoB1jxAyrrxtvOfse1k09npmZMzSS7ivpmynT9lWSjpB0x5q41ZI2pEzbl0g6RtIdGsY8RVKeZsHMzMymzExsaFRkqfwa8I2I2AHYEVgFvCuL656Ruipl2t4NuC/w3CVcrpmZmU3YrFxyehywMSI+DRARmyS9Cbha0tXAkyg2OCuAl3Y7pbif0M+0vSXwaWAP4DJgyyU9CjMzM1uQWdnQ1GXb/h9JP6M4xj2B3SPiuvRpwABIWgk8HPjbVPUa4KaIeIik3Smye5uZmdmUm4lLTmM4MSKuK5W3l3Q+cC3wXxFxYarfD/gcQKq7EDMzM5t6s7Khqcu2fWfg/sBtVDNtd++h2R7YS9LTl2SVZmZmtihmZUNzErCVpJcASFoBfBBYC9zU1Cki/hv4e+AfUlU50/auwO6Lt2QzMzOblJnY0ETxx/gHAs+RdCVwBbAReMsY3b9BsRl6NPBRYJWkS4F3kN2XY2ZmZtNpVm4KJiJ+Djytpmlt+urGrQd2LZWD4q+aup6/KAs0MzOzRTMTZ2jMzMzs9s0bGjMzM2s9Z9s2MzOz1vMZGjMzM2u9mbkpeDlsvPGWgFK21NLJrvzMVyUjbq+h+1DKjJs1VpMkZ5mCS+GRVc5nrH5owxrzecsZgDt5TFNm4GrW4mq24uF9i9cosrZs/qZMxBGN8+WZlwfqGzMpN9TXvEZUXqPh6ygyHufjNh1Xv0+3YuiaBmJLcWmNSjG9xyy2W1ZpLGVt9PpSiR0cuxzbbWsYKxuTiJq1ZMdQs/Z8Lf3HzmCfmkflWbyzR2VjDfRtyh5e6VtdV6Utfz2HzNvLft372c4yV/fa0yPlPqW6gdjeD8zAmBFR6jPGPOUxavoOm6e6nk465O5xRvZSpDL0+nSymKY+lXr6P2P5GMP6dF+Ofp9ubLbGSp/+2it9ujHd4yebn6itG9WnWx63b11c3XhFudMw5ui+H4v1s5ttW9KmlD17naSvSNpqRPxaSVenPhdIenxD3P6Sjl+cVZuZmdmkzMSGBtgQEWsiYlfgFuDVY/Q5JH1a8BuBjy3q6szMzGxRzcqGpuw04EGSVkta162UdLCkw2rizyRl205xT5J0maRzgb9Y9NWamZnZZpupDY2kLYAnAxfNo9uTKD4tuJt9+xMUH9C3F/DHk16jmZmZTd6sbGi2TNmzzwZ+Bhw9Rp8PSLoC+DzwvlS3E3B1RFyZPkH4c4uyWjMzM5uoWfkrpw3pfpgeSbcxuGFbmfU5JCK+KukNwKfIsnWbmZlZe8zKGZo61wLbSbq7pDsBT22I+wgwJ+mJwGXAaknbp7YXLME6zczMbDPN7IYmIm6lyJj9E+BEis1KXVwA7wQOjYiNwF8D3043Bf96iZZrZmZmm2EmLjlFxKqG+iOBI2vqD8rK/wH8R3r+XYp7aczMzKwlZvYMjZmZmd1+eENjZmZmreds22ZmZtZ6PkNjZmZmrTcTNwUvm403BFQzTGdpt7PHXkNzfUM25m5FJStzeayGPpX6atrtkX2irr3p2Cvz1NSP/dqM0bexT91xj7fmwWzb2Ti9dL35+Fl9J6p1w2LzQ6pk4G4aoyauaZ6GY4hStu1qRue8Pit3orK26DT1ramvG68UU8kQPk7fIWP2MjV3x6+sfXCpvQzsnf64/b6RxQ7Wl+PHnjc77knN2+kdRwy8JL1yKdN8J1tDuW1wLNJY/bE72XugLmawTG/Msdeaj9WpZr/Of2z6b/nolfMf5boYauNiSN/BddTFzWee5r6prjH7drnPqJj61ywGjrPpePL6fnkh8/X71s/3nTjqdpNt+1uS7toQt1bSs9PzUyRdnrJtnyHpwUu7ajMzM5uUmdjQMJht+zrgdWP2e1FE7AF8BvjAoq3OzMzMFtWsbGjKetmzVfhIOhPzfWC7hj6nAg9KfdZL2jY931vSKUuwZjMzM9sMM7WhkbQCeDxwXKo6EHgwsDPwEuCRDV2fxvwydJuZmdkUmZWbgrvZtu8DXEqR6gBgP+ALEbEJ+JWkk7N+x0raAKwH3rBUizUzM7PJmpUzNN1s238CiPndQ7MmIp4ZET9PdeUs3XmGbjMzM5tCs7KhASAibgL+BvhfkraguDfmeZJWSLoX8NgxhlkP7JWeP2tRFmpmZmYTNVMbGoCIOA+4EHgB8HXgSuAS4BiKG4ZHORw4QtLZwKbFWqeZmZlNzkzcQ5Nn246Ip5WKr2/os39D/WnAjhNbnJmZmS26mTtDY2ZmZrc/3tCYmZlZ6znbtpmZmbWez9CYmZlZ683ETcHLZeOmIs1rLyNuOcltlv20mlC6vh2iEltuGzXWuPN0s5jWJc5umidqxqoceyWmub1SN/YY/fWPO0an1D7RtTb1ZZz55tG3crzZcdWsY5zjqtRnMXkG8DzTeznTfCVzdENsJRv0vOYdrKeUYTmftxxTWU8l43j+wg6pn09sXj9ubJ4xPKK+rik2q69kK6/ENq81f+0rWczr5m34fm7WvE2Z5stZ3LtPK5nds/dPOQN7L6ZTH5OPUX4/jTtP3RijYurW2q3PYjrph6+Xwbqm3EkvYP93xmC52x5ZuRP9fNtN43fnrxszH69u/LH7pvmOi+Nrs23PxIZG0iaK1AWi+FPr10fED0f0OQW4F7ARuAF4WURcvshLNTMzs0UwK5ecutm29wD+AXjPmP2cbdvMzGwGzMqGpuzOwO8AJO0v6fhuQ8q8fVBNH2fbNjMza7GZuOREPznlSorLSI+bZ39n2zYzM2uxWdnQdJNTIukRwDGSdh2jn7Ntm5mZzYBZ2dD0RMSZ6ZLRPRjMnA3V7Nkvioizszpn2zYzM2uZmbuHRtJOwArgt8A1wM6S7iTprsDjxxhiPc62bWZm1iqzcoamew8NFH+6/dKI2AT8XNKXgXXA1cB5Y4x1OHC0pH8GTlmMxZqZmdlkzcSGJiJWDGk7FDi0pn7/hnhn2zYzM2uZmbvkZGZmZrc/3tCYmZlZ6znbtpmZmbWez9CYmZlZ683ETcHLZeOm6wPK2Yu7j/QzpZbrSuV+e7U+r6tmxm6uz+drXEc/RXHvv6PWlp/Ni9Sr1IXy6kfNRzZuv+9izluaZcx5Y6AujynKnSHtTa99P1lwc3slM/YE5u1k5X57eU3K1qgsVtlY0EGDaxvZp1+OEfMNG6tpvuF90vPe69aw9pqxK31Hzd+LU/XYY7Dc/75W549srY3z14xRybSeZbQuZ6Mv2qOStbxfrh+jv47oZYgev2/pfdtd0wLGqMaSjVUds6lPDOlTHGdzW/PxV+ete+2HzRs18+aZwkuDdSep1lWye+djbE7f3gs/fE119eWxG8bd8IO312bb9hkaMzMza73Wb2gk3VPS5yX9VNI5ks6UdOCIPuslXSTp/PT4jKVar5mZmU1eqzc0kgR8Azg1Ih4YEXsBzwfuO0b3x6b8T88GjlzEZZqZmdkia/WGhiKr9i0R8bFuRURcExEflnSQpK9J+q6kKyW9v2GMOwO/A5C0WtK6boOkgyUdtpgHYGZmZpuv7TcF7wKcO6R9DfBQ4Gbgckkfjoifp7YfpDM8DwSeu7jLNDMzs8XU9jM0AyQdJekCSWelqpMi4vqI2AhcAvxJKfyxEbErsBvwEUmrlnq9ZmZmNhlt39BcDOzZLUTE6ygyat8jVd1cit1EzRmpiLgKuBbYGbiNwddk5YTXa2ZmZoug7Ruak4GVkl5TqttqPgNI2g54AHANxcZmO0l3l3Qn4KkTW6mZmZktmlbfQxMRIemZwL9JOhT4DXAj8GZgyxHdfyBpE3AH4O8j4loASe8AfgL8Erhs0RZvZmZmE9PqDQ1ARPwXxZ9q11lbintq6fnqIeMdif+M28zMrFXafsnJzMzMzNm2zczMrP18hsbMzMxar/X30CyrjbcF1GQ+LdX1y+kxq+iXuw9BftIssqChY2VtTeuoHau0hsE1NY9Vl7G5HJv3rXuNKslY87XVvFYLnjfqxh89byUzbjZvJet1qb6ubnDebOxSfV1deW2VzNm9Oerr8uMq5u3Xl7Nn1x1vtdyvrxuvbt5OzXrGnbdT85qNmjd/DcuvTX8tWTlvL405TkxTe+OaxlhP//mYay61V463Yf5yeVjbqHLlezGP8rixw9Yc/Sd0X42B8sAvhPwXQaltaH1nHrF1j6Vx5jVvVOqiN0aeybpUX8lq3ZBdu66+ITaGzddb6wLma1xzUd505hecbdvMzMxm00xsaCRtSpmz10n6iqShn0Ujaa2kq1OfyyT901Kt1czMzCZvJjY0wIaIWJNSGdwCvHqMPoekbNtrgJdKesCirtDMzMwWzaxsaMpOAx40j8zZ3fQGN6a49ZK2Tc/3lnTKIq/XzMzMNtNMbWgkbQE8GbhojPAPSDof+AXwxYj49aIuzszMzBbNrGxotkybk7OBnwFHj9Gne8npj4HHS3rkYi7QzMzMFs+s/Nn2hrQ56ZE0VubsiLghXVbaF/ghgxm3nW3bzMysBWblDE2dsTJnp8tUDweuSlXrgb3S82ct9iLNzMxs883shiYibgW6mbNPpJo5u3sPzYUU99x8LdUfDhwh6Wxg0xIt18zMzDbDTFxyiohVDfW1mbMj4qAhY50G7DixxZmZmdmim9kzNGZmZnb74WzbZmZm1no+Q2NmZmatNxP30CyfKwL6GUf7eX+DyLK7ltuK/2Z9BuKGtfX79sfqxw1rq523HFdzHAPz5pmm+8NWMx53YxrKRcZjDY0dNlbdeIw55jhrK4/Vif7d4ZWMxylmU6W+374pGzeP2VSaJ3/stTX2HVxHuT7Paj3OWpvm6TSuoz9vY1tWH/nxznOevL25rblPU4LlSvLgmsfez0FDAuehfTsxvz7lpMV55vW8b8N6ImqCq+nNB8rqVOtqUp0PPKoc1xAzMH7d2DV9NZ+1p7ZKn+Yf8vq6YWsd+GXS9EtreL0Gvif18w6tr/zyGsx+3f83qV/O/53KY6npM27fuj7dMattMbRPeczKeGn+DT9ztm0zMzObUVO5oVHhdElPLtU9R9J3Jd1QqttB0vGSrpJ0jqQfSNpvjPG72bkvkHSuPyXYzMys3aZyQxPFOalXA/8qaaWkVcC7gdd1YyStBL4N/O+I2D4i9gLeADxwjCm62bn3AP4BeM/ED8LMzMyWzFRuaAAiYh3wLeDNwNuBYyLiqlLIi4AzI+K4cp+IWAsg6TBJn5J0iqSfSvqbhqnuDPwu9dlf0vHdBkkfkXTQJI/LzMzMJm/abwo+HDgXuAXYO2vbJbUNsxPwWGAb4HJJH02fINxNZrkSuBfwuImu2szMzJbUVG9oIuJGSV8CboiIm4fFSvo6sANwRUT8Rar+dup3s6RfA/cEfkEpmaWkRwDHSNp10Q7EzMzMFtXUXnIq6dD/A7ayi4E9u4WIOBA4CPijUkx5E7SJmg1cRJwJbAvcg8FM2+Bs22ZmZq3Qhg1Nk88Dj5L09FLdVvMdRNJOwArgt8A1wM6S7iTprsDjJ7JSMzMzW1RTfclpmIjYIOmpFH8J9SHgWuAPwDvH6N69hwZAwEsjYhPwc0lfBtYBVwPnLcLSzczMbMKmfkMTEYdl5VWl55cBfz5mv11Lz1cMme9Q4NCFrdbMzMyWQ5svOZmZmZkBzrZtZmZmM8BnaMzMzKz1pv4emqm28baAahZciP7zXlLULCarLyfFrqsrV+TJVwfqFzBfr75XN3jWLobU95PYdjOo1ow7UO4HjIxtOpYxxm9aT/l7U4kdMkY/eW/9uJ2GtXfK8zXFko1dqq+rK6+tk5UHE/JW6/LjKubt11ezXA/OUy3368fum61nOfpGVtd9H5Vfi9rymDFN7cPaBteYfe8iSs/HXHOpvZNlS+5kWZL7r1k/u3GnKTbLuNzpjdGfo5O1RTb+sPX0+zbM01BfvL55tufeu3ywXM7ePHZsXX0WM858jX3rYhrGzGPHSbk+LA183WNnINV7Q8wYY3WGrGnUWA2xnRN+7GzbZmZmNpumakNTyoK9TtJXJA39XBlJayVdnfpcJumfxpznSZJ+kvqcL+lLku4/maMwMzOzpTZVGxr6WbB3pcjf9Oox+hyS0hisAV4q6QHDglOKgw9TfPbMTqnvscDqzVu6mZmZLZdp29CUnQY8SNJqSeu6lZIOlnRYTXw3TcGNKW69pG3T870lnZLa3wy8OyIu7XaMiOMi4tQUe4qk96UzOFdIevTEj8zMzMwmaio3NJK2AJ4MXDRG+AfSp/7+AvhiRPx6RPw4Wbq3iIh9gDcCY13GMjMzs+UzbRuabkqCs4GfAUeP0ad7yemPgcdLeuS4k0m6e7qH5gpJB5eavpYez8GXoszMzKbetP3Z9oa0OemRNFYG7Ii4IV1W2hf4IYOZs8t9ulm6L4iI3wJr0mZmVSmmm6W7NkO3mZmZTZdpO0NT51pgu3Q25U7AU+uC0mWqhwNXpar1wF7p+bNKoe8H3irpIaW6eWfpNjMzs+kx9RuaiLgVeAfwE+BE4LIspHsPzYUU99x0LxcdDhwh6WyKMy3d8S4C/hY4RtLlks4AHgJ8flEPxMzMzBbNVF1OKWfSzuqPBI6sqT9oyFinATs2tH0b+HZD2/6l5/+N76ExMzObelN/hsbMzMxsFGfbNjMzs9bzGRozMzNrvam6h6ZtNm4q0oPm2YsHnmdZkvvVMTKuqS2y0cpx1XnyMapr7ZUb15oe82zbRKWtsrY8O3X5WcOa+hnB6+ujtNhqW358g1mLo7Tq/mszaqyoZGzuZwmO2nKnpm8/43Aew2C5FNfUt3GsUsbnyNbS1LccV1dXlAczHdetq98nz4o86rXqVF/PUWsfyOw8fPy6tfe/t53Gccv1UarPx+u1NYxZru80xuTzDmbBLs+bx+SZrOvXnPfJYjvVvtU+3Td/wzylsSp18yj3nndGzT9szU3vYyrt1T7VmNoxh8aMHqOfZHqeYwx8P+kOkoIh60xpsYMxjX1q2svj1MVWMmaX6kf2GTJ/w9rixF8427aZmZnNplZvaErZuS+QdO44nxIsaQtJ75Z0Zep7vqS3LsV6zczMbHG0/ZJT75OFJT0ReA/wmBF93kmRJmG3iNgoaRvgfy3uMs3MzGwxtfoMTebOwO8AJO0v6fhug6SPSDpI0lbAK4E3RMRGgIj4Q0QcluJWS7pU0ickXSzpe5K2XPpDMTMzs/lo+4Zmy3TJ6DLgk8A/j4h/EPCziPjDkJgdgKMiYhfg9wymTTAzM7Mp1PYNzYaIWBMROwFPokhnUHv3cx1Jf5U2RD+XdL9UfXVEnJ+eO9u2mZlZC7R9Q9MTEWcC2wL3YDDTNvSzbf8ncP903wwR8el0D871wIoUc3Opn7Ntm5mZtcDMbGgk7USxKfktcA2ws6Q7Sbor8HiAiLgJOBr4iKSVqd8K4I7Ls2ozMzObhLaffdgyZdoGEPDSiNgE/FzSl4F1wNXAeaU+b6W412adpD8AG4DPAL8C7r1kKzczM7OJafWGJiJWDGk7FDi0pv5W4O/TV249sGsp9l82f5VmZma22GbmkpOZmZndfjnbtpmZmbWez9CYmZlZ67X6Hprl96uAftbXUprQgazS3bpyOcj79DPJLrhv3byxkL71M8AkJQAAIABJREFUMf3svfTqm7JpV+qzTMhRW5dlmW0ai+gFzX/euizfo+fNMzlXMuX2MjlXx6irg3KS2SwjcKm+k6+tqW9NXKWukoWarG80rqkpy3inZr5OZa0N9UMzg4+/jrHnK9VXx61/HSuZvKOa3buaCXxI31FZxWte1+4cdePVzkN1/krG5s7gcda1N2V/pjJGNa65bfT8o2Ka569fy+BrRvZY+o1ZWUtTuT/mQvuW582/12P17f0cZAsYltm6sliqMeVyXbbtUX3qyo1rGmOMhj7xvUucbdvMzMxm00xtaFQ4XdKTS3XPkfRdSTeU6naQdLykqySdI+kHkvZbnlWbmZnZ5pqpDU0U5+heDfyrpJWSVgHvBl7XjUkfqPdt4H9HxPYRsRfwBuCBy7FmMzMz23wzdw9NRKyT9C3gzcDWwDERcVUpxdOLgDMj4rhyH4oP4UPSYcD9KTY49wc+FBFHLt0RmJmZ2XzN3IYmORw4F7gF2Dtr2yW1DbMT8FhgG+BySR9NH8hnZmZmU2gmNzQRcaOkLwE3RMTNw2IlfR3YAbgiIv4iVX879btZ0q+BewK/WNRFm5mZ2YLN1D00mQ79PxgruxjYs1uIiAOBg4A/KsU447aZmVmLzPKGpsnngUdJenqpbqvlWoyZmZltvtvdmYeI2CDpqRR/CfUh4FrgD8A7l3dlZmZmtlAzu6GJiMOy8qrS88uAPx+z3651cWZmZjY9bo+XnMzMzGzGONu2mZmZtZ7P0JiZmVnreUNjZmZmrTezNwUvkYC6lPVRWzfuY5v6bs58nc7gxwRN87yTeF3bMO8k3z/TPO+449eNNW6f/HJ+2+adb5/yvPP9Pi7nvHWv17jzzrfvcs477P0x7lqnaF5Ro1VnaCStlrSupv6TknZejjWZmZnZ8puJMzQR8YpJjCNpi4i4bRJjmZmZ2dJp1RmaZAtJx0q6VNJXJW0l6RRJewNIukHSuyRdIOlHku6Z6p8m6ceSzpP0/VL9YZI+K+kM4LOSTpW0pjuZpNMl7bEsR2pmZmZjaeOG5sHAv0fEQ4D/AV6btW8N/Cgi9gBOBV6Z6k8H/jQiHgp8ETi01Gdn4M8i4gXA0RS5nZC0I7AyIi5YpGMxMzOzCWjjhubnEXFGev45YN+s/Rbg+PT8HGB1en5f4ARJFwGHALuU+hwXERvS868AT5V0B+BlwNqJrt7MzMwmro0bmhhRvjX6t0SXM2V/GPhIROwGvApYWepzY2+wiJuAE4FnAM8Fjp3Qus3MzGyRtHFDc39Jj0jPX0hxKWkcdwF+mZ6/dETsJ4EjgbMi4nfzX6KZmZktpTZuaC4HXifpUuBuwEfH7HcY8BVJ5wD/PSwwIs6huD/n05uxTjMzM1sirfqz7YhYD+xU07R/KaacVfurwFfT828C36wZ87C8TtK9KTZ739vMJZuZmdkSaOMZmkUl6SXAj4G3RkRnVLyZmZktP2fbNjMzs9bzGRozMzNrPW9ozMzMrPVadVPwFApY/OzB09x3c+Zztu3pm3eS759pnnfc8ach6/VyzTvfPuV55/t9dLbtxZ/X2baXkKR3SPqzIe3PdEZtMzMzqzM1G5qIeHtEfH9IyDMpci4tCkk+W2VmZtZSy7KhkfSPki5Pmay/IOlg/X/27jxclqq89/j31/uABwFBcQgOeCKiCMgsEUSDaIwaHNBjNDGaoyaRRMThYkKuJBKVRIMD4pQ4IKhovOCEOOAAKDLIDAcEHEEiCYIMogLC3u/9o1Z1V1dXT3v3VH1+n+fhqaq11rvWqu59tsuq2vVKx0lam+rfJun7ki6T9A5J+wDPBo6SdImkbSv63FbSRYXj7fJjSf8s6XxJl0v6kCSl8jMkHS3pAuA1qY9zJa2X9FZJv57IB2JmZmYrMvGrEpIeBzwf2AXYCLiILIlkXr8VcCCwfUSEpC0j4lZJJwOnRPayvA4R8WNJt0naNSIuAV5G602/74uIN6f+PwEcAHwp1W0cEXumulOA90TEpyUdNOJTNzMzszGZxhWaJwBfjIg7I+J2WguL3G3AncBHJT0P+O0QfX8EeJmkBeCFwKdS+ZMlfS9l2t6f9kzbnyns702WbZtCrJmZmc24mXmGJhcR9wB7kaUsOAD42hDhnwWekeIujIhfSloNfABYG1mm7Q/TJdO2mZmZ1dM0FjRnAc+StFrSZmSLj6ZUtkVEfAV4HdmtKYDbgc17dRwRdwKnkiWszG835YuXm1Lfa3t0cS7Z7TCAFw12OmZmZjZtE1/QRMT5wMnAZcBXgfVkt5lymwOnSLoM+C7w+lT+X8AbJF1c9VBwwQnAEimxZETcSnZV5nKyxc75PWJfC7w+jf3I0rzMzMxsRk3rT5XfERFHSLo38B2y20MfLtTvVQ6IiLMY7M+29wU+FhGLhdjDgcMr+tyvVPRz4PHpYeQXAY8eYDwzMzObsmktaD6UXpK3Gjg+Ii7qFzAISZ8HtiV78Hc59gDel/6s+1bg5aOYl5mZmY1XLbNtS3o/2V9LFb0nIj5W1d7MzMzmWy0XNGZmZmZFM/dn22ZmZmbDcv6iFZAUaUt5W1U26HbWY3ONRqNn3bzEFtv1a1P32GE/k7rGDvMzPmzsvIw76d8l0xp3EuPNwrjL/R2yku9kXOMC7R9oPlZV4TTI2bbNzMxsmWZmQTOpbNtyVm0zM7O5MzfZtlPc41LMJZKOknR5Kl8n6WRJpwHfkrSZpG9JukhZZu3npHZvlvTaQn9HSnrN2D8QMzMzW5G5ybadfAz464g4R9LbSnW7AztHxM3pKs2BEfErSfcHzk39Hwt8DjhaUoMs/UHHS/7MzMxstsxNtm1JWwKbR8Q5qaicLfsbEXFz3hz4V2UpDr4JPAR4UERcA/xS0m7A04CLI+KXw52emZmZTdrMPU8SEfdI2gt4ClkiyYNZ/pt/i4pZtV8MPADYIyLulnQNrSSWHwHWAb9HdsXGzMzMZtzcZNtOSShvl/QHqahXtuwtgF+kxcyTgYcX6j4PPB14HFkySzMzM5txE79CExHnp+dVLgNuoDrb9hclrSa7NVTMtv1hSYcAayPixxXdvyK1WQK+Tfds2ScAX5K0HrgAuKowv99JOh24tZjg0szMzGbXvGXbviIidgaQdBjZYoWIOA44rtDXTcDeVR2kh4EfD7xg0JMxMzOz6ZqrbNvAn0j6R7LzupbsWZiBpTmdAnw+In44ojmZmZnZmNUyOaWcbdvMzMwKarmgMTMzMyuamdQHZmZmZss1c++hqRM52/ZA2XPrHltsV4eM2SuJHfYzqWvsMD/jw8bOy7iT/l0yrXEnMd4sjOts22ZmZmY1sEEuaOSM22ZmZnNlLv+HXdI/AX8B3AhcR5b88gDgEmBf4NOSfgAcDmwM/JIsHcKNwNXAPhFxo7J30vwA2Dsibpz4iZiZmdlA5u4KjdqzeT8D2LNQvXFE7BkR7wS+Czw+InYjewvx30fEEvBJssUNwFOBS72YMTMzm23zeIWmmc0buFNSMZv3Zwr7DwU+I2lrsqs0P03lxwJfBI4GXg743TZmZmYzbu6u0PRRzLj9XuB9EfFY4JWkbNsRcR1wg6T9yVIwfHXiszQzM7OhzOOCpmc274ItgJ+n/b8s1X2E7NbTiU5QaWZmNvvmbkETEecDeTbvr9KZzTt3BHCipAuBm0p1JwOb4dtNZmZmtTCPz9BA/2zeRMQXyZ6VqbIL2cPAV415nmZmZjYC87qgWXY2b0mHAX9L6y+dzMzMbMY5OaWZmZnV3tw9Q2NmZmYbHi9ozMzMrPbm9RmaiVDKtp0n/qzOEtol02ieLLSiXWeG0Uaf2Fa77plLG31i1X2uHeMOMdce59t3rj3Ot+9cm7GNitg+c60434HnWjHngeda8R0NPNeK8x14rs3hBI0BM+E2KmK7tum2pdWu7zijnbNaHQw957xN1zl37ati3IHn3mPOA3xWzdghPqu2z3jIz6rtux1yzh3jLmfO6d9Qo0vbYnmj8DlNMrZVNrrYqrb5cWd/449t/4xGEZuCmfNs25LWSLp82vMwMzOzyZubBY2ZmZltuOZtQbNK0gmSrpR0kqR7S3qKpIslrZd0rKR7AUi6RtK/SLoo1W2fyjdN7c5Lcc+Z7imZmZlZP/O2oHk08IGIeAzwK+D1wHHAC1POplVk75jJ3RQRuwMfBA5NZW8ETouIvYAnA0dJ2nRC8zczM7NlmLcFzXURcVba/yTwFOCnEfGDVHY88KRC+8+l7YXAmrT/NOAwSZcAZ5C9nG+bMc7ZzMzMVmje/sqp/JbAW4GterS/K20XaX0WAp4fEVePeG5mZmY2JvN2hWYbSXun/T8HLgDWSHpkKnsJ8O0+fZwKvFrp78Qk7TaWmZqZmdnIzNuC5mrgVZKuBO4LvBt4GVlW7fXAEvAfffp4C7ARcJmkK9KxmZmZzbC5ueUUEdcA21dUfQvouMoSEWsK+xcA+6X9O4BXjmOOZmZmNh7zdoXGzMzMNkDOtm1mZma15ys0ZmZmVnte0JiZmVntzc1DwdPw8JRte9XGGwOwUb69172a+6sWFgBYSNvmcaPRvi2UN/KyPMNoqW23+obUtl+u61fezGzaLaYi82neT69Mrd2Oh2lbLu9oAwPFto1biukVm7ft1W+3eXSr6xc7yFx79dk3ppQJmWJG51I27XLG4+b/FSpmGy63yTflcTrKe4yr9lhVjTtIm24xXcbrHD8/VPc2jUKbckx+XPouKtt0m0eXtoPE9jyfYiyF2K6fRbm813lSajTAOQwZ294+32+0x9L+e6pYXlVW1bZ13Op70NjqeZX77Tb3qnbDtF3uXKvGG6RtuXyYtq15Vc1ZHT8U7TaoKzSSPiJphz5tjpO0dlJzMjMzs5XboK7QRMRfTXsOZmZmNnpzeYVG0hpJV1Vk3j5D0p6pza8lHSnpUknnSnpQRT9vSVdsFiZ/FmZmZjaouVzQJOXM239Xqt8UODcidgG+A/x1sVLSUcADgJdFxOIE5mtmZmbLNM8LmnLm7X1L9b8DTkn7xWzbAP8EbBERB4Vf1GNmZjbz5nlBU16IlI/vLixWitm2Ac4H9pB0v3FNzszMzEZnnhc05czb3x0i9mvA24AvS9p85DMzMzOzkZrnBU058/YHhwmOiBOBDwMnS9pkDPMzMzOzEZnnP9u+JyL+olS2X74TEZsV9k8CTkr76wrlxwLHjnWWZmZmtmLzfIXGzMzMNhDOtm1mZma15ys0ZmZmVnte0JiZmVntzfNDweOn9G4bpdt2xW1V2aDbWY/NX+nTqIgp1vWNXUp1LCN2guMqBmzTL7Y07lCxExp30M9zoNgZHnfgn/GKvvrOaal0PETsLI078M9axbhD/y6Z4rhVn9eg4w4bO81xGz1+PvqN21E25XGJDTvbtqRnSzps2vMwMzOz0dsgrtBIWhURJwMnT3suZmZmNnq1WtBI2hT4f8BDgQXgLcDbU9kzgDuAP4+IH0k6DrgT2A04S9JlwJ4RcXCq+xWwJ/B7wN9HxEmSGsD7gP2B64C7gWPTe2rMzMxsRtXtltPTgesjYpeI2IksRQHAbRHxWLLFyNGF9g8F9omI11f0tTVZwsoDyNIcADyPLEnlDsBLgL0r4szMzGzG1G1Bsx74I0lvl/TEiLgtlX+6sC0uQk6MiMUufX0hIpYi4vvAg1LZvilmKSL+Fzh91CdgZmZmo1erW04R8QNJuwPPBN4q6Vt5VbFZYf83Pbq7q7Bf+cS0mZmZ1UOtrtBIejDw24j4JHAUsHuqemFhe84KhjgLeL6khqQHUcj9ZGZmZrOrVldogMcCR0laIntg92/JkkreNz30exfwZyvo/7PAU4Dvkz0UfBFwW88IMzMzm7ra53KSdA3ZXy/dNKL+NouIX0vaCjgPeEJ6nqaisV+s17Oub6xfrDd47ITGHfTzHCh2hscd5gVo5b6GeQHasLGzNO7AP2t+sZ5frDfhcbu8WK9uV2gm4RRJWwIbA2/pupgxMzOzmVH7KzRmZmZmtXoo2MzMzKyKFzRmZmZWe36GZgV0xCsDQOnxpOazTmrfL9f1O5712Hyn0aeuMjZpaBmxKxl3BbEqTL4x7Oda7H8Z38myx11mbDFu6Ng8aBnnu6JxlxE7yOfWra+277bX3MY17hj+bVeNW/mz3Gu8XrErGXcZPwvDjNvz326vPpfxnQw07gi+z2X9Hug13jK/k4HGXcb3Cf9Z+kTTWFWFZmZmZnXiBU0fyvhzMjMzm2Ez8T/UkjaV9GVJl0q6XNILJV0j6f6pfk9JZ6T9IyQdL+lMSddKep6kf5e0XtLXJG2U2l0j6d8kXSLpAkm7SzpV0o8lHVQY+w2Szpd0maR/SWVrJF0t6ePA5cDDJv6hmJmZ2cBmYkFD9yza3WwL7A88G/gkcHrKtn0H8CeFdj+LiF2BM4HjgLXA44F84fI0YDtgL2BXYA9JT0qx2wEfiIgdI+LalZ+imZmZjcusLGi6ZdHu5qsRcXeKW6C1AFoPrCm0O7lQ/r2IuD0ibgTuSi/Pe1r672KyNAfbky1kAK6NiHNXeF5mZmY2ATPxV05dsmjfQ2vBtboUcleKW5J0d7TeDrhE+zndVSgvZtfO2wn4t4j4z2LnktbQO1O3mZmZzZCZuELTJYv2NcAeqcnzxzT0qcDLJW2W5vEQSQ8c01hmZmY2JjNxhYbqLNqbAB+V9BbgjHEMGhFfl/QY4Bxlf+D+a+AvgMVxjGdmZmbj4VxOK+AX6/Wuq4xN/GK9ybycathYv1ivf19t322vuY1r3DH8264a1y/W6zPeMr6TgcYdwfe5rN8DvcZb5ncy0LjL+D79Yj0zMzObW75CY2ZmZrXnKzRmZmZWe17QmJmZWe3Nyl851ZOU3a/reKqqS9mg21mPzTX61M1LrIZoU/fYYT+TusYO8zM+bOy8jDvp3yXTGncS483CuMv9HbKS72Rc4xLlT7RtqNqS9FxJO0x7HmZmZjY9tV/QAM8FvKAxMzPbgM3kgkbSFyRdKOkKSX+Tyn5dqF8r6ThJ+5AlqDwqZdXeVtIZkvZM7e4v6Zq0vy71+42UiftgSa+XdLGkcyXdL7U7I+WUOk/SDyQ9ceIfgJmZmQ1lJhc0wMsjYg9gT+AQSVtVNYqIs8kSUL4hInaNiB/36Xcn4HnA44AjydIt7AacA7y00G5VROwFvBZ408pOxczMzMZtVh8KPkTSgWn/YbQyYK/U6RFxO3C7pNuAL6Xy9cDOhXafS9sLgTUjGtvMzMzGZOYWNJL2A54K7B0Rv5V0Blm27eIbAMvZt4v6ZulOihm4u2XpXmQGPyMzMzNrN4u3nLYAbkmLme2Bx6fyGyQ9RlIDOLDQ/nZg88LxNbSydK8d92TNzMxs+mZxQfM1YJWkK4G3Aeem8sOAU4Czgf8ptP8v4A3p4d5tgXcAfyvpYuD+k5u2mZmZTYtzOa2EX6w32Iuy6h47ipdE1SV22M+krrHD/IwPGzsv4076d8m0xp3EeLMwrl+sZ2ZmZjb7fIXGzMzMas9XaMzMzKz2vKAxMzOz2vM7VlZASu/GSc8Gtx5civb9cl2/41mPzV8J1OhTNy+x+TFAYxmf61hjy+UrHLcYN5OxFee7nHEH+cy79TXOf2Md4xY/o0mOu8xxho3tGLc41wmNO8nft23j9vm3O+pxl/v7ZyU/C23jLuN8u9QFR8z/Q8GSviJpyz5t1kl68KTmZGZmZuM3VwuaiHhmRNzap9k6YKgFjSRfyTIzM5thtVrQSHqDpEPS/rslnZb295d0QsqifX9JayRdKenDKWP31yVtImktWcLLE1J27k0k7SHp2ym796mStk59niHpaEkXAK+Z2kmbmZlZX7Va0ABnAk9M+3sCm0naKJV9p9R2O+D9EbEjcCvw/Ig4CbgAeHFE7EqW9+m9wNqU3ftYsizcuY0jYs+IeOfYzsjMzMxWrG63Ui4E9pB0H7IEkheRLWyeCBwC/GOh7U8j4pJC3JqK/h4N7AR8QxLAAu1pFT4zysmbmZnZeNRqQRMRd0v6KdlzMGcDlwFPBh4JXFlqXsysvQhsUtGlgCsiYu8uQ/5mRRM2MzOziajbLSfIbjsdSnaL6UzgIODiGPyVx8Xs3FcDD5C0N4CkjSTtOOL5mpmZ2ZjVdUGzNXBORNwA3JnKBnUc8B+SLiG7xbQWeLukS4FLgH1GO10zMzMbN+dyWgG/WK9P3bzE+sV6MxRbcb5+sd4Yxl3mOMPGdoxbnOuExvWL9fof+8V6ZmZmZpPhKzRmZmZWe75CY2ZmZrXnBY2ZmZnVXq3eQzNrlJ4m7XheMarLBt3OemzzGdqKmGJd39ilVMcyYic4rmLANv1iS+MOFTuhcQf9PAeKneFxB/4Zr+ir75yWSsdDxM7SuAP/rFWMO/TvkimOW/V5DTrusLHTHLfR4+ej37gdZVMel8APBQ9L0hGSDp32PMzMzKw3L2jMzMys9uZ6QSPppZIuk3SppE+kLNynpbJvSdomtassNzMzs3qY2wVNSmFwOLB/ROwCvIYss/bxEbEzcAJwTGrerdzMzMxqYG4XNMD+wIkRcRNARNwM7A18KtV/Atg37XcrNzMzsxqY5wWNmZmZbSDmeUFzGvACSVsBSLofcDbwolT/YlpJLbuVm5mZWQ3M7XtoIuIKSUcC35a0CFwMvBr4mKQ3ADcCL0vNu5WbmZlZDcztggYgIo4Hji8V71/R7tou5UeMZ2ZmZmY2SvN8y8nMzMw2EM62bWZmZrXnKzRmZmZWe17QmJmZWe3N9UPB4/Zz3pjdr4uUTpRsq4jWfp5etdkmUnk6jtIxgUpt89hmX23jFI6JwcepGHfQcZp9x9LA41R9HsONM9i43T73trEG+Szaxm0WFcYpHZfv3LaVl9o025bLK/ru2W9VTEX5QHNMO8uZY7nvqn7b+qgoH+Q8Rjpee7d9j6vKh+2jqs9hYpYzx2H7WOkc+423nJhlnHfHkxSDjDfK8+xzHCs53+XEDhHT87Ob4GfUK3bhiKh/tm1J75b02sLxqZI+Ujh+p6T/K+mkHn1sKenvCscP7tXezMzMZl+tFjTAWcA+AJIawP2BHQv1+wCnRcTaHn1sCTQXNBFxfZ/2ZmZmNuPqtqA5myzvEmQLmcuB2yXdV9K9gMcAN0u6HLIElZLOk3RJyqS9HfA2YNtUdlTKtJ23XyPpTEkXpf/2mfwpmpmZ2bBq9QxNRFwv6R5J25BdjTkHeAjZIuc2YD3wu0LIQcB7IuIESRsDC8BhwE4RsStki5hC+18AfxQRd6bFz6eBPcd7VmZmZrZStVrQJGeTLWb2Ad5FtqDZh2xBc1ap7TnAGyU9FPhcRPxQqnyWKLcR8D5JuwKLwKNGPHczMzMbg7rdcoLWczSPJbvldC7ZFZp9yBY7TRHxKeDZwB3AVyR1pDcoeR1wA7AL2ZWZjUc6czMzMxuLOi5ozgYOAG6OiMWIuJnsQd+9KS1oJD0C+ElEHAN8EdgZuB3YvEvfWwD/ExFLwEvIblGZmZnZjKvjgmY92V83nVsquy0ibiq1/VPgckmXADsBH4+IXwJnSbpc0lGl9h8A/lLSpcD2wG/GcgZmZmY2Us7ltAJ+sZ5frOcX61X07RfrDd7nKF9MNoo+VjrHfuMtJ2YZ5+0X65WOh4jxi/XMzMzMpsgLGjMzM6s933IyMzOz2vMVGjMzM6u9Or5Yb2ZsKgW0/rY7Xx0udCmrOq57bK/+5il2kM+vbrGq6mSYH5g6xy7nH8g0Ywf5wR117HK+i2nHNn+oVw2xHaZtt9iFIWKmNe4oxpv2uM0ly4b9UHAxZ9OA7ddJevA452RmZmajscEsaJZhHeAFjZmZWQ1saAuaBUkflnSFpK9L2kTSrpLOTdm4P58yd68lS31wQsrKvcm0J25mZmbdbWgLmu2A90fEjsCtwPOBjwP/EBE7k71x+E0RcRJwAfDiiNg1Iu6Y2ozNzMysrw1tQfPTiLgk7V8IbAtsGRHfTmXHA0+ayszMzMxs2Ta0Bc1dhf1FsqSWZmZmVnMb2oKm7DbgFklPTMcvAfKrNb2ycpuZmdkM8Xto4C+B/5B0b+AnwMtS+XGp/A5gbz9HY2ZmNrs2mAVNRFwD7FQ4fkeh+vEV7T8LfHb8MzMzM7OV2tBvOZmZmdkc8ILGzMzMas/Zts3MzKz2fIXGzMzMam+DeSh4HJSybeerwuK2qmzQ7azH5mlOF/rUzUtso9FK4rvQaJUNuq1TbL4/77HNpMx9B1ioGFDDxwwcO65x8/0h+uio6xZbNddBY8c0busLTluVjvNt1W+EfrHF3xTDxk5z3K6/4QYYt1/MpMedo2zbkl4g6UpJpw8Rc4akPYdov6ukZy5vhmZmZjZJtVzQAK8A/joinjzGMXYFvKAxMzOrgZm/5STpC8DDgNXAe4DfA/YFPirpZOAK4LnApmTJJ98BbEz21t+7gGdGxM2puxdI+gBZyoNXRMSZklYDHyTLrn0P8HrgLODNwCaS9gX+LSI+M4nzNTMzs+HN/IIGeHlE3CxpE+B84A+B/YFDI+ICSevIXpi3G9mi50dk2bN3k/Ru4KXA0amvVRGxV7qV9CbgqcCrgIiIx0raHvg68Cjgn4E9I+LgiZ2pmZmZLUsdbjkdIulS4FyyKzXbVbQ5PSJuj4gbyfIzfSmVrwfWFNp9Lm0vLJTvC3wSICKuAq4lW9CYmZlZTcz0FRpJ+5FdRdk7In4r6QyyqzBlxSzaS4XjJdrPMS9fZMbP3czMzAY361dotgBuSYuZ7anIuTQCZwIvBpD0KGAb4GqcbdvMzKw2Zn1B8zVglaQrgbeR3XYatQ8ADUnrgc8A6yLiLuB0YAdJl0h64RjGNTMzsxFx6oMV8Iv1etfNS2zdXo63ktg6vRxvJbF+sd4AffjFel1i/WK96Y87Ry/WMzMzMyvygsbMzMxqz7eczMzMrPZ8hcbMzMxqz+9iWYH8oeDyo0yi+2PCmZi6AAAgAElEQVROgxyPMrbbI2mjiu02p2Fih5ljv3GHiR1m3OXMsVvsOMft9RlN6nOdZGyvfy8D/ayXnjNVaVt+7lSN1jOq3WLzmKr6frG9xpWqY8rPyFaOm+936aNq3I5+SrGVz6rm20GeFe3Wx6CxPcfNJ5/+J06r2o/z7cJGnWXND6FL7MJGreNhY8c2bqmPqnGL8cPEVs51yuP6oWAzMzObVzOzoJH0ZklP7VH/XEk79OnjDEl7jmAuW0r6u5X2Y2ZmZpMxMwuaiPjniPhmjybPBXouaEZoS8ALGjMzs5qYyoJG0j9JulrSdyV9WtKhko6TtDbVv03S9yVdJukdkvYBng0cld7cu22P7l8g6TxJP5D0xNTfgqSjJJ2f+nxlKt9M0rckXSRpvaTnpD7eBmybxjpqjB+FmZmZjcDEHwqW9Djg+cAuwEbARWTZr/P6rYADge0jIiRtGRG3SjoZOCUiTuozxKqI2EvSM4E3kSW3fAVwW0Q8TtK9gLMkfR24DjgwIn4l6f7AuWmcw4CdImLXkZ68mZmZjcU0/srpCcAXI+JO4E5JXyrV3wbcCXxU0inAKUP2/7m0vRBYk/afBuycXwEiS3q5HfDfwL9KehJZZu6HAA8acjwzMzObspn7s+2IuEfSXsBTgLXAwcD+Q3RxV9ou0jo/Aa+OiFOLDSWtAx4A7BERd0u6Bli9/NmbmZnZNEzjGZqzgGdJWi1pM+CAYmUq2yIivgK8juzWFMDtwObLHPNU4G8lbZTGeJSkTcmu1PwiLWaeDDx8BGOZmZnZhE38Ck1EnJ+eU7kMuAFYT3abKbc58EVJq8murLw+lf8X8GFJhwBrI+LHQwz7EbLbTxdJEnAj2V9NnQB8SdJ64ALgqjTHX0o6S9LlwFcj4g3LO1szMzObhKnkcpK0WUT8WtK9ge8AfxMRF018IivkNwX7TcF+U/B0Y/2mYPymYL8puLOPDfRNwdN6huZD6SV5q4Hj67iYMTMzs9lRy2zbkt5P9tdSRe+JiI9NYz5mZmY2XbVc0JiZmZkVzdyfbddJ+Rma/B6zpNb95lRbrCseN/JjKmIr6qr6at6XRz3resZKHeM0ynOumEejPCe6nF9FX73qesaqNU7HHEvzqKpvnl/F+bSdf6G+6/c3wPfb7fvr9/02iuP2+/4q6vt9f1X1XesG+H4H/v4q6of9XIvf7yDfX8dn06Ou7fwr5jHM91eu7/rvot+/m17/tgf4fvt+90N8roN8v73+7ULv77fvd9/j+x343/ZAn2v7Z1LVrlxXCGo/pqK+V13VMRWxVXX95jHMOHn9csYpxy7nfLvVPf5fSp1lZiaXk5mZmdlyeUEzAEkL/VuZmZnZtNRiQSPppSmp5KWSPiFpjaTTUtm3JG2T2h0n6T8kXZCSUx6QytdJ+qKkMyT9UNKbCn3/hbJklpdI+s988SLp15LeKelSYO+pnLiZmZkNZOafoZG0I3A4sE9E3CTpfsDxZH/ufbyklwPHkL0oD2ANsBewLXC6pEem8r2AnYDfAudL+jLwG+CFwBPS24I/ALwY+DiwKfC9iPg/kzhPMzMzW76ZX9CQ5XE6MSJuAoiImyXtDTwv1X8C+PdC+/8XEUvADyX9BNg+lX8jIn4JIOlzwL7APcAeZAscgE2AX6T2i8Bnx3ZWZmZmNjJ1WNAMq/x36NGjXGRXev6xop87I2Jx1JMzMzOz0avDMzSnAS+QtBVAuuV0NvCiVP9i4MxC+xdIakjaFngEcHUq/yNJ95O0CdntqbOAbwFrJT0w71vSwzEzM7NamfkrNBFxhaQjgW9LWgQuBl4NfEzSG8gSTb6sEPIz4DzgPsBBEXFnup10HtktpIcCn4yICwAkHQ58XVIDuBt4FXDtRE7OzMzMRmLmFzQAEXE82YPARft3af7NiDioovy/I+K55cKI+AzwmYryzYaeqJmZmU1FHW45mZmZmfVUiys0g4qIdV3KjwOOm+RczMzMbHKcnNLMzMxqz7eczMzMrPbm6pbTpL278fyAVmbZhhrNbVUZwEKX8mL7YdqWt0PHpNSyWtVAq7IyLTSaZZXHhfL+bdS1r+WMV47NU+Oq0d6mWZ7HFOu71uWpgBsd9b3qsm2qr+gz3++oy2Oa59CeUVYNtepUattKW9ylXNX9dWnbrB+mLYWXO6k1Tp4ZN1SoK5Tnx1Eub6srZ+Lt0UeXbL4d/Rf6al2XXkrnEWm7lEe3HUczYqmibZc+oqqP4cfLj8ttl9JrsrpuWUzTWBygzVJHfV6Xl0WfPlrtlvq2aW6X8uOl5vFidJa1x2Tlix19LPaoaz+/xYqYzrou4zfLl1hayr+LaJtbZ3mpPqJQFqV+y+Wjic3LollGdpy2zfr8OPL6qGjLwH0V++nZNkp9V4ybt7nqw9dvGNm2JS2mvEyXSzpR0r1T+dmSVku6StJjC+3fIOk/0/52kk6R9GNJF0o6XdKTpnUuZmZmNpi5W9AAd0TErhGxE/A74CCAiNgnIu4EXgt8QJmHpPrDJK0Gvgx8KCK2jYg9yN5384jpnIaZmZkNah4XNEVnAo+ELHs2QER8Dfgf4KXAu4EjIuIWsjcOnxMRJ+fBEXF5+gspMzMzm2Fz+wyNpFXAM4CvVVS/luzNwT+MiE+ksh2BiyY0PTMzMxuheVzQbCLpkrR/JvDRcoOIuF7SacAp3TqR9HlgO+AHEfG8bu3MzMxs+uZxQXNHROw6QLslaP7ZAMAVQPMB4Ig4UNKewDtGPD8zMzMbsXl/hmYYnwKeIOnZhbJ7T2syZmZmNrh5vEKzLBFxh6QDgHdJOhq4AbgdeOt0Z2ZmZmb9zN2CpluW7HJ5Vd6niLgKeOZ4ZmZmZmbj4ltOZmZmVnte0JiZmVntOdu2mZmZ1Z6v0JiZmVntzd1DwZP0ZB2Qsm3nmasL2bYb5bKF9uNGnlG71K6x0Nlfod+8DcBCR3mjo01nbJftQqOZQTnPJN3Is0PnGbObbVvtGqW6Vmw5o7U6+mx0yXY92LilfktZtxvN8s52g7RpO5eGKtpUx1S1699GXY+bZerepttxniG7XNc1Rhqq/6wgbaTm/z3Kx20mvy5l7O4sH7BNob46ttymPJ9ShnI6s1sv5VmvozordkQU2pbadIlp9Rkd45VjlirGy49b/ZYyLPfbsjRU2/x4kDbdtv3aLjYzW6fjpdZxr7ostkv50mKhTb8+CuP1qKuKbZ7D4lIru3cpm/ZiKet26ziPjcHbljN1LwWLi73bVPXZjF/MM2H32y41j8t1S31joxC7NHDbztgudd/47/nMtt0ju3ax/EuStizEOKu2mZnZHKn9goYu2bVL5TcDrwJwVm0zM7P5M2+3nM4Edq4oP6dQXplVG7gcQNIRwDZkC5xtgKMj4pgxztnMzMxWaB6u0ABt2bXXl8oXgKcA+QJmkKza2wN/DOwFvEnSRqOdrZmZmY3SPCxo8uzaFwA/o5VdOy//X+BBwDeqgiV9Pj1n87lC8Zcj4q6IuAn4RYo3MzOzGTUPC5r8WZldI+LVEfG7YjnwcLK/xXhVKr8C2D0PjogDgXXA/Qp93lXYX2T+bs2ZmZnNlXlY0PQUEb8FDgH+T7ot5azaZmZmc2buFzQAEXExcBnwZxFxB3AAcJCkn0g6BzgcZ9U2MzOrrdrfShkiu/azCvtds2pHxBGl451WPkszMzMbpw3iCo2ZmZnNNy9ozMzMrPacbdvMzMxqz1dozMzMrPZq/1DwNL1gt41Ttu3suLhNCZWbZQvNzMedbdvaNdRZ162vivpiP5XjdJ1Xo5ANuj0rdK/yVhbvCcc2M1ZnWcW1sNB23CgdF+sbC6uq6xbyDOWdMUoxVXU9YxdWdZ9TeavSOWkBetX1iS3XMUDsIP0Wj6OZbrtBK711/v+ThjmebGx+XXop30Z7tuu8PMrl0b4PnZmy8/LWcZ4luzhO9zaV8ymMm7dpZYdOGZWj/XipcNxss9S9TbmvpS4x5fGWKsbvHKfUppRZuritKituWxmrh49drIgdOKZXButlbLvW5Z/ZcmIHicnvyqTj5jZKx80f8KXB2nTrcyk6yyrbVsyr3Db/d3LmxfOZbRvaMmtfKukiSfssp62zcJuZmdXTvFyhyd8KjKQ/Bv4N+MNiA0mrIuKebm0LWbgPzRNXStoJ2BP4zsTOxMzMzIY2LwuaovsAtwBI2g94SzreHnhUt7b0ycJtZmZms2teFjR5IsrVwNbA/oW63YGdIuKnfdoOkoXbzMzMZtBcPENDK0Hl9sDTgY9Lyh8aOq+wmOnXtqlLFm4zMzObQfOyoGmKiHOA+wMPSEW/GbDtIFm4zczMbAbN3YJG0vbAAvDLIds6C7eZmVlNzdszNAAC/jIiFivuJHVtC9wh6QDgXZKOBm4AbsdZuM3MzGbeXCxoImKhS/kZwBmDtE11XbNwm5mZ2eyau1tOZmZmtuHxgsbMzMxqz9m2zczMrPZ8hcbMzMxqby4eCp6WI/bdJGXbzq5ytWXb7pJNu1vW6+rYGDim67gDxOTtmlmtmwmUS9mum21bx602eX/tx+oW2xDqKGvvo5kkuqKPvKxr5uoe264Zsxur+seUt10zaLeyc/ebU54FG61qP24sgPL9VKdyTKm+WN6t33Ifxb679VuKyc8vmpmsF5pfWORt1WiP7VEfDB+TH3fUpb56xqQs4c0Ev3kW32by4NJxM2t0Z1k5ZqlbfURn3VJ12475RBT2U5t8jvm4PY6b/Q3QNh9/4LbNz6p1PHhsewbrLCt02l/srKs8XqyILbft0VdVP73GjUKfzZjUf5SOW/UptlDeGVMdGxV99RuvZ0wpE3fkWdOXFrset9oulj6Tckxnu3LMIOP1i70sTpnfbNvQlkX7ckknSur5DhllDpf0Q0k/SJm1d5zUfM3MzGx05mZBQyulwU7A74CD+rR/FbAPsEtEPIos6/bJKet2Gyn/v3ZmZmY2i+ZpQVN0JvBISWskNbNlSzpU0hHp8B+AgyPitwAR8XXgbLKs20j6taR3SroU2HuiszczM7OhzN2CRtIq4BnA+h5t7gNsGhE/KVVdQJZ1G2BT4HsRsUtEfHcskzUzM7ORmKcFTZ7S4ALgZ8BHV9jfIvDZFc/KzMzMxm6e/srpjojYtVgg6R7aF22rASLiV5J+I+kRpas0ewDfTvt3Rv6ItZmZmc20ebpCU+UG4IGStpJ0L+CAQt1RwDGSNgGQ9FRgX7Ks22ZmZlYj83SFpkNE3C3pzcB5wM+BqwrV7wXuC6yXtAj8L/CciLhj8jM1MzOzlZibBU1EbNal/BjgmIryAP4l/Tdwf2ZmZjZ75v2Wk5mZmW0AvKAxMzOz2nO2bTMzM6s9X6ExMzOz2pubh4Kn4SCtybJtp+MF5Vu17Zfr+h0PG1scf9jxmpmsFxpoIc9g3SoDmuWNvH6hENPoLKuMaZTLG137zdu2ysvHao3T7Le0LZUX23e0LcW0zmGha0yj27gV43efaznrdd6uUF5VVuiLhXJ5oa+qsmLbivE7MoB3G3+hnMm6UUyx3j5eOet1VbtSG/Xrq1g/SJuOvvJs2+0ZlVtZr6u3WQbg/m261Q8zTrm8X5tex8O0LZ/nJGKL26qyQbeTigFYXFysLOsXUx53mJhBY3vFlNvk30Wv42Halo/H8X3+/Oc/n89s26Us21+StGWXdsdJWpv2V0n615Rp+5L03xsnO3MzMzMbldovaGjPsn0zWRbtft4KPBh4bHq78BOBjcY4RzMzMxujebvldA6wM4Akkb0874+A64DfpfJ7A38NrImIOwEi4nbgiFT/ZuDmiDg6HR8J/CIi3jPRMzEzM7OBzcMVGgAkLQBPAU5ORQcCjwZ2AF4K7JPKHwn8LC1iqhyb2iOpAbwI+OSYpm1mZmYjMA8LmjzL9v8CDwK+kcqfBHw6IhYj4nrgtKpgSS9Lz9BcJ+lhEXEN8EtJuwFPAy6OiF+O/zTMzMxsueZhQZNn2X442Z8u9HuG5kfANpI2B4iIj6X424D05xF8BFgHvIzsio2ZmZnNsHlY0AAQEb8FDgH+j6RVwHeAF0pakLQ18ORCu48C75O0Gpq3qzYudPd54OnA44BTJ3cWZmZmthxz9VBwRFws6TLgz8iee9kf+D7wM7IHhnNvBN4CXC7pduAO4Hjg+tTP7ySdDtwaEYsTPAUzMzNbhtovaMpZsSPiWYXDg7vE3A0clv7rkB4GfjzwghFN08zMzMZobm45jYqkHcies/lWRPxw2vMxMzOz/mp/hWbUIuL7wCOmPQ8zMzMbnLNtm5mZWe35lpOZmZnVnm85rYCzbTvb9oaebTvSz1Nb1uu0jXKW6476QmxjuNi2PiqzaffuI78uvZR2Oo7zbNDkx3l9VLRt1VX3lY6JQtt+4+TziuZxlOa6uJTXpQzHzQzWtB9HsJj3uxQdddlxZ30+h1a/rblU9lGo76xr/4wWSzHFbb5/T0Vd+3apa2x526uv7v132RY+j0hl+Tb/jJqZ0cvlhfpWGe1tS7FVfXftt/Q5F/totU0Zz5cWe26XCsetuhS72Du2uF0qlw0R21mWjf+7i491tu1Ctu0zJF2d4q6U9DeTnbWZmZmNUu0XNCwv2zbAi9Mbgp8AvF3Sxv0CzMzMbDbNw4Km6BzgIZBl25b0vnQl5pvAA7vEbAb8BlhMcb/OKyStlXTceKdsZmZmKzU3z9AUsm1/NBUVs20/iOyNwcW8TCdIugvYDnit3whsZmZWX/NwhWa52bZfHBE7A9sAh0p6+MRmbGZmZiM1DwuaYbNtt4mIG4GLgD/IiwrVq0cyQzMzMxureVjQAINn2y6TdG9gN+DHqegGSY9J+ZwOnMDUzczMbIXm5hkaGCrbNmTP0NwB3As4LiIuTOWHAacANwIXkD00bGZmZjOs9guaZWbb3q9HfycBJ41kcmZmZjYRc3PLyczMzDZcXtCYmZlZ7TnbtpmZmdWer9CYmZlZ7dX+oeBp+pQeHQBqZq5ubRuNzrLK7UpiK/oYNraZLbuhzszZjfZs18W2ebuuMY1yBu3OvlpZvfvEVJTnGaybJ1+KaaUTbx+Xhrq3LWX7Lvahjv5KX1yPPqv6a2vb60vq9YPSN3bYGA3ctnlOPbJtlzNot7Utt+vIiK0ufVRsq+bSbZzmccrInbZL0X4csVA6Tu1oECy0lVW16dZHr7r2+XTWR2nO5QzWeRbsquNB2hS3izFYv93H692mI4N3YbtUqitnFc+ziXfEFjJYL1bUdYvpaNs3Jo2/uFQ5/7btYjlj9lLrPEttypmzl8oxhXblcaKjr6VSH4Vs26U55T9I0aU+FqP5ofdskw3UUd+rrt98OurS9qLv/V39sm0Pm0lb0pGS3l4of7ikn0jaMmXY3jOVXyNpfep7vaTnTOqczMzMbPRmekHD8Jm03wo8V9Jj0vF7gH+KiFsr2j45vWF4LXDMyGZsZmZmEzfrC5qivpm0I+IO4HXA+yU9E9g8Ik7o0+99gFtSv2skXZ5XSDpU0hGjPxUzMzMbpVo8QzNMJu2I+IqkVwDHA/v26PZ0SQIeAfzpmKZuZmZmEzDrC5o8k/ZDgCupyKQNXC+pnEn7/cAmEXF1j76fHBE3SdoW+JakM0Y8dzMzM5uQWb/ltNxM2kvpv74i4sfADWRXe+6h/TNxtm0zM7MamPUFDbD8TNqDkPRA4PeBa8kWNg+UtJWkewEHrHz2ZmZmNm6zfsupachM2oM4XdIisBFwWETcACDpzcB5wM+Bq0YxdzMzMxuvmV7QLCeTdmp3BnBGqWy/wv6aHrHH4D/jNjMzq5Va3HIyMzMz68ULGjMzM6s9Z9s2MzOz2vMVGjMzM6u9mX4oeNY527azbY8n23bVF1puu5LYXj98g7VtZdsubPtm2+6RBXugDNldtsOMUzwGltLrqiJSduK0DUrHeT1LbfvTiC236cxo3VneLKPcdrQxeXlnTHvbxY7s2zSPF0tZtVt10dG2XN+1bqlbbFTOod8cIcvonbdZLPXfOu5evxjlNnSJ6azvVddt3HLW8ma26wG2zf2VxC6jj87Y7Dzjg+fWK9v2GDNtbybpg5J+LOkiSRdK+utJnZeZmZmN3swuaBhfpu2PkCWj3C4idgeeDtxvhPM2MzOzCZvlBU3RSDJtp7xNewGHR7p+GxE3RsTbU/1+6WrOSZKuknRCSmBpZmZmM2zmFzSFTNsnp6Jipu2XAvvkbSPiK2RXX44H/q6iux2BS/PFTBe7Aa9N/T8CeMIKT8HMzMzGbJYXNHmm7f8FHkRFpu2IuB6oyrR9fp9M2wBIemN6Tuf6QvF5EfHfadFzCbBmpSdiZmZm4zXLC5pxZNr+PrCLlP2ZQ0Qcmca4T6HNXYX9RfyXYGZmZjNvlhc0wGgzbUfEj4ALgLemW1lIWk22YDIzM7OaqsXVhxFn2v4r4CjgR5J+CdwB/P0Ip2tmZmYTNrMLmjFm2v4V8MpBYiOi6zhmZmY2O2b+lpOZmZlZP17QmJmZWe0527aZmZnVnq/QmJmZWe3N7EPBdfCxxlMCiomJ8+zRhf28LmVaXigd94pdWCjVdYstHC8U+in3W9lXW9LiaO5n29KxoiOmo02j1Ebd67v130qO3H0+ef/Otu1s28vLtp2dT565Osiz+fY5ZqmVLbiUMbvYJivvPF7OeOVYqM4cvRQqlatZv1jY79c2K1f3tpT7asXkx4P0X3UOi9E9m3ZntuvO+r4xFdthY5rntghLS+m88u1i6bhH/XJiWrH0jq2MST/zi1lsI51geavFznKV26YPvxnTUd8rtktMRX23OR7/hZfMdrbt9NbeKyRdlt7e+wcj7Pv/LjOumaXbzMzMZtdMLGgk7Q0cAOweETsDTwWuG+EQlQualOhyJj4DMzMzW75Z+R/zrYGbIuIugIi4KSKul3SNpH+XtF7SeZIeCSDpAZI+K+n89N8TUvlmkj6W2l8m6fmS3kbKC5WyZ69Jmbo/DlwOPEzSByVdkK4Q/cu0PgQzMzNbnllZ0HydbGHxA0kfkPSHhbrbIuKxwPuAo1PZe4B3R8TjgOcDH0nl/5S3T1d6TouIw0h5oSLixanddsAHImLHiLgWeGNE7AnsDPyhpJ3HerZmZmY2UjPxUHBE/FrSHsATyXIzfUbSYan604Xtu9P+U4EdpOZzQfeRtFkqf1Gh31u6DHltRJxbOP5TSX9D9nlsDewAXLayszIzM7NJmYkFDUBELJKlHThD0nrgL/OqYrO0bQCPj4g7i30UFjj9/KYQ8/vAocDjIuIWSccBq4edv5mZmU3PTNxykvRoSdsVinYFrk37Lyxs80SUXwdeXYjfNe1+A3hVofy+afduSRt1Gf4+ZAuc2yQ9CHjGcs/DzMzMpmMmFjTAZsDxkr6fsmrvAByR6u6byl4DvC6VHQLsmR78/T5wUCp/a2p/uaRLyW5fAXwIuEzSCeWBI+JS4GLgKuBTwFkjPzszMzMbq5m45RQRFwL7lMvTLaSjIuIfSu1vonXlplj+a1q3qorl/wAU+9ipVL+uy7z26zt5MzMzm7pZuUJjZmZmtmwzcYWmm4hYM+05mJmZ2exztm0zMzOrPd9yMjMzs9qb6VtOs+4Jz/p2QOv9N3kG4kajlWG5XKdGqW1FfVV/bW2a9Xnm7Fa5Spmcq/ov9tEoHHePLc+Zjrk2Sv225lYup9l3x1wK/bbPkY45q9S2GVsxTlZOsy9VlLXFtifFzhI6l+qq2rTPo7WtKqtqWx0bfWKja3mzjG5tS30TnXWUx4/qPomeddXH+fyis65bTKm8QRTqlgaLJVpto1QXS32PW/vtbSjHRGcfzbbl2CidQ0W7vD9K/dOvz1jq26bZ51LhuEsblsrzqCjvExNLPfoeNGapPas5S61xm207+qiIreqn0LY8bhTrS7HlcaOjr7SNpR5tusQUyodp24ppL1ta7N1Hq74Qm8qWyuOl7NvNmEJsuWwp7+vudHxPdD3uqEvbA+65erazbQ9C0hGSDp32PMzMzGy21GpBM2qSfIXKzMxsDkx0QSPppelleJdK+kTKfH1aKvuWpG1Su8ryQj8PlHRh2t9FUhRifyzp3pKeJel7ki6W9M30FuD8Ks8nJJ0FfELSOklfkPSNlN37YEmvT3HnSrrfJD8jMzMzG97EFjSSdgQOB/aPiF3I3vz7XuD4lBn7BOCY1LxbOQAR8QtgtaT7kCW0vAB4oqSHA7+IiN8C3yXL97Qb8F/A3xe62AF4akT8WTreCXge8DjgSOC3Ke4c4KUj/BjMzMxsDCZ5y2V/4MT0ll8i4mZJe5MtJAA+Afx72u9WXnQ28ATgScC/Ak8HBJyZ6h9KlrV7a2Bj4KeF2JMj4o7C8ekRcTtwu6TbgC+l8vXAzss4VzMzM5ugOj9D8x2yqzMPB74I7ALsS2tB817gfRHxWOCVtGfQ/g3t7irsLxWOl/BfgpmZmc28SS5oTgNeIGkrgPRsytnAi1L9i2ktRrqVF50J/AXww4hYAm4Gnkl2qwlgC+Dnab8jv5OZmZnNj4ldfYiIKyQdCXxb0iJZhutXAx+T9AbgRuBlqXm38mJ/1yh7cch3UtF3gYdGxC3p+AjgREm3kC2mfn88Z2ZmZmbT5tQHK+AX6/nFen6xnl+s5xfr+cV6frGeX6xnZmZmNhJe0JiZmVnt+ZaTmZmZ1Z6v0JiZmVnt+R0rK6D0dGD+UGlxW1U26HbWY/OHORcWetfNS2z2IHH/NvMQO8xnUufY/MFemg9xDrFdTsywsYuL2bb4oOqkY4c9v1mOrfpM8m2vunmKHaTfusRGbJgPBae8UJdPex5mZmY2PnO/oBkFZ+U2MzObbRvKgmaVpBMkXSnpJEl/KOlzAJKeI+kOSRtLWi3pJ6n8DElHS7qALJGmmZmZzagN5crDo4FXRMRZko4ly6q9a6p7InB5KlsFfK8Qt3FE7DnRmZqZmdnQNpQFzXURcVba/yRwCPBjSY8B9o8aVCkAACAASURBVALeRZa1e4H2vFGfmegszczMbFk2lFtO5ZftBFkOqGcAdwPfJMvUXczWDZ1Zuc3MzGwGbSgLmm0k7Z32/5wskeWZwGuBcyLiRmArsltT/osoMzOzmtlQFjRXA6+SdCVwX+CDZM/KPIhWtu7LgPXhVyebmZnVztw/QxMR1wDbd6m+V6Hd35Ti9hvfrMzMzGyUNpQrNGZmZjbHvKAxMzOz2nO2bTMzM6s9X6ExMzOz2pv7h4LHSXpWuryV0vs2t42Ksqo23eoHadOtr+WMl2/rMF63cYfpa7DxpOx41apWBueNNqJZNui2TrH5/rzHNkhZfO+5Z/jtcmK6xd59d7bNswn3qh9l7LTPs9fxMG27xKZvd6DtMG3rHFunufaLPWJes21LerOkp46gn69I2nIUczIzM7PJqv0Vmoj45xH188xR9GNmZmaTN5NXaCRtKunLki6VdLmkF0raQ9K3JV0o6VRJW6e2x0lam/bfJun7ki6T9I5C/QclnSvpJ5L2k3Rsyrx9XGHMayTdP+2/NPVxqaRPTOEjMDMzsyHM6hWapwPXR8SfAEjaAvgq8JyIuFHSC4EjgZfnAZK2Ag4Eto+IKN0+ui+wN/Bs4GTgCcBfAedL2jUiLin0syNwOLBPRNwk6X7jPFEzMzNbuVld0KwH3inp7cApwC3ATsA3JEH29Ob/lGJuA+4EPirplBSX+1Ja5KwHboiI9QCSrgDWAJcU2u4PnBgRNwFExM0jPjczMzMbsZlc0ETEDyTtDjwTeCtwGnBFROzdI+YeSXsBTwHWAgeTLU4A7krbpcJ+fjyTn4GZmZkNblafoXkw8NuI+CRwFPAHwAPyjNmSNkq3hooxmwFbRMRXgNcBuyxz+NOAF6RbWPiWk5mZ2eyb1asTjwWOkrQE3A38LXAPcEx6nmYVcDRwRSFmc+CLklYDAl6/nIEj4gpJRwLflrQIXAysW+6JmJmZ2fjN5IImIk4FTq2oelJF23WFw7161afM2zt1qVtT2D8eOH6YOZuZmdn0zOQtJzMzM7NheEFjZmZmteds22ZmZlZ7vkJjZmZmtTeTDwXXxT1f/vxcXt762taPm/YURm7rbX427SmM1P2uefi0pzAWa+7znWlPYeT0qEdNewojdf3Vt017CmPxe43lvuljdv3m9zae9hTGYvPNN69Xtm1Ji5IuSbmcTpR072X0sS6906Zfu2I+qIMl/UhS5LmdzMzMbLbN7IIGuCMido2InYDfAQcto491QN8FTclZwFOBa5cxnpmZmU1BXW45nQnsDCDpC8DDgNXAeyLiQ5IWgI8CewIBHAtcl45PkHQHWXLKHYB3AZsBNwHrIqItJ1REXJzGmcBpmZmZ2SjM/IJG0irgGcDXUtHLI+JmSZuQZcv+LFmCyYekqzlI2jIibpV0MHBoRFwgaSPgvfTI2G1mZmb1NMsLmk0k5VmwzyS7AgNwiKQD0/7DgO2Aq4FHSHov8GXg6xX9PZr+GbvNzMyshmZ5QXNHROxaLJC0H9nzLXtHxG8lnQGsjohbJO0C/DHZszZ/SueVF9EnY7eZmZnV0yw/FFxlC+CWtJjZHng8QPprpEZEfBY4HNg9tb+dLGklZFdxembsNjMzs3qq24Lma8AqSVcCbwPOTeUPAc5It6g+CfxjKj8O+I9UvgCsBd4u6VLgEmCf8gCSDpH038BDgcskfWSM52NmZmYjMLO3nCJis4qyu8geEK6ye7kgXbH5bKHoEvpk7I6IY4BjhpyumZmZTVHdrtCYmZmZdfCCxszMzGrP2bbNzMys9nyFxszMzGpvZh8KroNTrrtog7q89cwbfzrtKUzURav3nfYUJuoxv7ln2lOYmF/t+PNpT2Gitl7csM73V7duM+0pTNQPfzHtGUzWHnvsUa9s22ZmZmaDmtkFjaRFSZdIulzSiZLuvYw+1knqm21b0nGS1qb9EyRdncY9NuWAMjMzsxk2swsaUuqDlHDyd2QpDYa1Dui7oCk5AdgeeCywCfBXyxjXzMzMJqguz9CcCewMIOkLZEkpVwPviYgPSVogS165JxDAscB16fgESXcAewM7AO8CNgNuAtZFRFuCyoj4Sr4v6TyyNwabmZnZDJv5BY2kVWRvB/5aKnp5RNwsaRPgfEmfBdYAD0lXc5C0ZUTcKulg4NCIuCDdOnov8JyIuFHSC4Ej6UximY+7EfAS4DXjPD8zMzNbuVle0GyScjBBdoXmo2n/EEkHpv2HAduRJZ58hKT/z959x8tV1/kff73nJhAgkCAgUg0ivQUCSJOiiKKIILiIumx0VVwLu3b2t4jo/vyJq6tSxUosCAiiREAEKQoRJIQ0QihKEWwIAtJJcj+/P873zD137rRbpt37fj4e8XvOt5+5M8PXc86czxnA5cBVVfrbBtgRuFoSZLGd/lylXu5s4NcRccOojsLMzMxarpsXNM9GxMxihqQDgYOBvVPE7euBKRHxmKRdgNeS3WvzTww98yJgWUTs3WhgSZ8GNgCOH/VRmJmZWct1803B1UwDHkuLmW2BvQAkrQ+UUjDKkxgIVPkksHbavgvYQNLeqc1kSTtUDiDp3WQLo2Mjor+lR2NmZmZjopvP0FRzJfA+ScvJFig3p/xNgHMl5Qu0/0zpHOCcwk3BRwOnS5pGduxfBZZVjHEO8ABwU7o0dUlEfLY1h2NmZmZjoWsXNBExtUre82Q3CFezW2VGOmPz40LWImD/KvVmF7a79jUxMzOz6nrtkpOZmZnZEI62bWZmZj3PZ2jMzMys5/l+kVE4f+FDXX966z9/tLjTU6jpjOPv6PQU6vrMr77X6SnUdPMLH+r0FBr6yyn/3ekp1LTxeUd1egp1la4/rdNTqGn+rO7+3ALM+eKNnZ5CXWf9unv/0zH3bV/p9BQaOvyHyx1t28zMzMannlrQDDcCt6QrJE0fxXgHSrpspO3NzMysPXpqQcMwI3BHxOsj4vFinjK9dtxmZmZWRy//h/0G4OWQReCWtEDSMknvzStIul/S+pJmSLpL0veA24HNJB0i6SZJt6WzPVNTm9dJulPSbcCbO3FgZmZmNjw9uaApROBemrLeFRGzgN3JgleuV6XZVsDZEbED8DRZiISDI2I34FbgI5KmAN8E3gjMAl7S2iMxMzOzsdBrv3IaTgTuRyvaPhAReaiEvYDtgXkpvMFqwE3AtsB9EXEPgKQfAO/FzMzMulqvLWiajsBdpe3TxWbA1RFxbEVfMzEzM7Oe05OXnCpUjcDdwM3AvpLye3DWkrQ1cCcwQ9KWqd6xtTowMzOz7jEeFjRXApNSBO5TGYjAXVNE/A2YDZwvaQnpclNEPEd2ienydFPwwy2btZmZmY2ZnrrkNNwI3BExI20+AuxYUXYtsEeVNleS3UtjZmZmPWI8nKExMzOzCc7Rts3MzKzn+QyNmZmZ9byeuoem25xyyykT6vTWAX98S6en0FYHvGhup6fQVqUDqj2Pcnza+0MbdnoKbXXl2Qs7PYW2Wnjs1zo9hbY6f60jOj2Ftvr617/uaNtmZmY2PvXMgkbSEZIiPWumHePNlrRxO8YyMzOz0emZBQ3ZQ+5upH0Pu5sNeEFjZmbWA3piQZMiYe8H/Cvw1kL+JyUtlbRY0qkp7+WSfpnybsuf+ivp45LmS1oi6TMpb4ak5ZK+mSJ1XyVpDUlHkwW6PE/SIklrtP2gzczMrGm9clPwm4ArI+JuSY9KmgW8OOW/IoU9eFGqex5wakT8JEXPLkk6hCxg5Z5kcZzmStof+EPKPzYi3iPpR8BREfEDSR8EPhYRt7b3UM3MzGy4emVBcyxwWtq+IO0LODcingGIiL9LWhvYJCJ+kvKeA0gLmkOA/Fb/qWQLmT+QRdfOI3gvAGa0/GjMzMxsTHX9giadeXkVsJOkAPqAAC4aTjfA5yPi6xV9zwCeL2StAnx5yczMrMf0wj00RwPfj4iXRsSMiNgMuA94AninpDUhW/hExJPAQ5KOSHmrp/JfAO9K9+IgaRNJL24w7pPA2i06JjMzMxtDvbCgORb4SUXej4GNgLnArZIWAR9LZf8MnJCiaP8GeElEXAX8ELhJ0lLgYhovVuYA5/imYDMzs+7X9ZecIuKgKnmnF3ZPrSi7h+wSVWWb0xi4D6dox0KdLxW2f0y2cDIzM7Mu1wtnaMzMzMzqcrRtMzMz63k+Q2NmZmY9r+vvoelmm5574oQ6vXXtr77Y6Sm01bfWvbTTU2irj/xieaen0Daf/tSZnZ5CW50y+aFOT6Gtrp+/Saen0FbXP35op6fQVo62bWZmZuNWTy5oJK1KP6delmI2fVTSsI4lxXG6vUr+ayQtSDGiFkga8ospMzMz6y69esnp2YiYCZAekPdDYB3g0800llTvuB8B3hgRf5K0I9lD+SbW+UszM7Me05NnaIoi4mHgvcAHlZkh6YYUafs2SfsASDow5c8F7ij2IellkhZK2iMiFkbEn1LRMmANSau39aDMzMxsWHr1DM0gEXGvpD6yCNwPA6+JiOckbQWcD+yequ4G7BgR96U4Tkjahizg5eyIWFzR9VHAbRHxPGZmZta1xsWCpsJk4ExJM8mCTW5dKLslIu4r7G8AXAq8OSIqz9rsAHyBLEq3mZmZdbGev+QE2SUjssXLw8CHgb8Cu5CdmVmtUPXpiqZPAH8A9qvob1Oy+FHHRcTvWzRtMzMzGyM9v6CRtAFwDnBmZI89ngb8OSL6yQJV9tVp/gJwJHCcpLel/qYDlwMnRsS8lk7ezMzMxkSvXnJaI0XYngysBL4PfDmVnQ38WNJxwJUMPSszSEQ8Lekw4GpJTwE7Ay8HTpZ0cqp2SLr52MzMzLpQTy5oIqLmWZcUbXvnQtYnU/71wPWFeveTIm1HxOPAHqloLvB/x3K+ZmZm1lo9f8nJzMzMzNG2zczMrOf5DI2ZmZn1vJ68h6Zb/HGTzcbl6a2j3v2tTk9hzL1419M7PYUx9YZzj+30FFri+F3/udNTGHunzOr0DMbU+cfU/Z1Fzzpyh691egpj7nsvubvTU2iJ9773vY62bWZmZuPTuFzQSPqvFIl7SYrK/Yo6dWdL2riw/0FJv5MUktZvz4zNzMxsNMbdJSdJewOHAbtFxPNpUbJanSazgduBPCDlPOAyCj/xNjMzs+427hY0wEbAI3lAyYh4BEDSLLKH700FHiFbyOxLFh7hPEnPAntHxMJUv/0zNzMzsxEZj5ecrgI2k3S3pLMlHSBpMnAGcHREzAK+A3wuIi4GbgXeHhEzI+LZDs7bzMzMRmjcnaGJiKfS2ZhXAgcBF5I9+XdHsvAGkMV3+nPHJmlmZmZjatwtaAAiYhXZPTDXS1oKfABYFhF7d3RiZmZm1hLj7pKTpG0kbVXImgksBzZINwwjabKkHVL5k8DabZ6mmZmZjaFxt6Ahu+n3u5LukLQE2B44GTga+IKkxcAiYJ9Ufw5wTvp59xqSTpD0ELApsETS+HvKnJmZ2Tgz7i45RcQCBhYrRY8A+1ep/2Pgx4Ws09M/MzMz6xHj8QyNmZmZTTCOtm1mZmY9z2dozMzMrOeNu3to2un4G344oU5vnT3/mk5Poa1OW+/fOj2Ftnrbw891egptc93hp3V6Cm11rO7p9BTa6k9/e0+np9BWtz320k5Poa0OO+wwR9s2MzOz8WlcLmhGGW37PEl3Sbpd0ndS2AQzMzPrYuNuQVMRbXtn4GDgwTpNZgMbF/bPA7YFdgLWAN7dmpmamZnZWBmP99CMNtr2FXlHkm4he8CemZmZdbFxd4aGMYq2ndr8M3BlB47BzMzMhmHcnaEZw2jbZwO/jogbWjhdMzMzGwPjbkEDo4+2LenTwAbA8S2bpJmZmY2ZcXfJabTRtiW9G3gtcGxE9Ldp2mZmZjYK4/EMzVTgDEnTgZXA74D3At8ATpc0jey4vwosYyDa9rPA3sA5wAPATeny1CUR8dl2H4SZmZk1b9wtaMYg2va4e03MzMzGu3F3ycnMzMwmHkfbNjMzs57nMzRmZmbW87ygMTMzs57nG2BH4cu339z11+s+suMjnZ5CTdddvU2np1DXK39zTqenUNPndn1np6fQ0Kf6vtLpKdR0xfard3oKdR362EmdnkJNv5/6VKen0NCD5z/U6SnUNf0DUzo9hZpmlX7U6Sk09qKvqlr2uDxDM8po29+WtDi1vVjS1PbM2szMzEZq3C1oxiDa9ocjYpfU9g/AB1s1VzMzMxsb4/GS02ijbf8j1RewBtD1l5XMzMwmunF3hoYxiLYt6VzgL8C2qZ2ZmZl1sXG3oImIp4BZZOEO/kYWbft4BqJtLwJOAjat08c7yS5DLQeOafWczczMbHTG4yWnUUfbzvuQdAHwCeDclkzUzMzMxsS4O0Mzmmjbyrw83wYOB+5s2+TNzMxsRMbjGZrRRNveF/iupHUAAYuBf2v7EZiZmdmwjLsFzRhE2963RVMzMzOzFhl3l5zMzMxs4nG0bTMzM+t5PkNjZmZmPc8LGjMzM+t54+6m4HaaceLlPX+97v4pb+v0FEZkpy027/QURu1Hn1/Z6SmM2LUHntXpKYzKc499udNTGLFjtvhkp6cwat+ack2npzBir9z/+52ewqi8XT9uXKnL/eWgmeMn2rak6ZLe36DODEm31yj7oKTfSQpJ6xfyJen0VLZE0m5jPXczMzMbez25oAGmA3UXNA3MI4vC/UBF/qHAVunfe4GvjWIMMzMza5NeXdCcCmwpaZGkr0i6RtJtkpZKelOh3iRJ50laLuliSWsCRMTCiLi/Sr9vAr4XmZuB6ZI2av3hmJmZ2Wj06oLmROD3ETET+DhwZETsBhwE/G8KWwCwDXB2RGwH/IPGZ3U2AR4s7D+U8szMzKyL9eqCpkjA/5O0BPgl2QJkw1T2YETMS9s/APbrwPzMzMysxcbDr5zeDmwAzIqIFZLuB6aksspfITX6VdIfgc0K+5umPDMzM+tivXqGphwhG5gGPJwWMwcBLy3U2zyPsA28DbixQb9zgePSr532Ap6IiD+P5cTNzMxs7PXkgiYiHgXmpZ9lzwR2l7QUOA64s1D1LuADkpYD65J+tSTpBEkPkZ2BWSLpW6n+FcC9ZBG6v8nofkllZmZmbdKzl5wiopknwm1bo+3pwOlV8gP4wCinZmZmZm3Wk2dozMzMzIocbdvMzMx6ns/QmJmZWc/zgsbMzMx6Xs/eFNwNWh1t+ytH7N7K7gE48sqtWzvAfq35odhOf7ysJf0WffCA41ra//6v+05L+9/uwye0rO+zFm7Tsr4Bdj30JS3t/6YffqKl/QPsdcihLen3pffs3JJ+i9Y/YHpL+z/1t62N+Py6172uZX0//czbW9Y3wEs3b+3vUvZ78FUt7R/g85u+uKX9v3OrjR1tu1B2nqS7JN0u6TuSJqd8R9s2MzPrQT25oGH00bbPI/tJ907AGsC7U76jbZuZmfWgXl3QjDba9hUponYAt5A9YA8cbdvMzKwn9eqCZkyibadLTf8MXJmyHG3bzMysB/XqgqZoNNG2zwZ+HRE3tGWmZmZm1hLj4VdOI4q2LenTqd3xhXJH2zYzM+tBvXqGZlTRtiW9G3gtcGxE9BfqO9q2mZlZD+rJBc1oo20D55Bdlrop3Vh8csp3tG0zM7Me1LOXnEYZbbvqcTvatpmZWW/qyTM0ZmZmZkWOtm1mZmY9z2dozMzMrOd5QWNmZmY9r2dvCu4G++z3f1p6vW6jjbZvZffZGBvv2NL+d505rSX93nRPayPeAmy3XWujXmy3U2v732jqri3r+9rTz2pZ3wC77jqlcaVR2H7TNkQ0Wbc1UY2//eHzWtJv0XZrr9va/l+yRUv7X3eP1r33z7xoecv6Bth+emtfm+023a6l/QNM37W1n68t3rld70XbbndUbUkHSrps7I/EzMzMWqmrFzQ4qraZmZk1odsXNJ2Iqr2OpMvTmZ1zJHX7a2RmZjbhdft/rDsRVXtP4EPA9sCWwJvH+qDMzMxsbHX7gqaoXVG1b4mIeyNiFXB+lb7MzMysy/TSr5zaEVV7m3p9mZmZWXfq9jM0nYiqvaekLdK9M8fkfZmZmVn36uoFTYeias8HzgSWA/cBP2nFsZmZmdnY6fpLTu2Mqh0R1wP7D2d+ZmZm1nldfYbGzMzMrBmOtm1mZmY9z2dozMzMrOd5QWNmZmY9r+tvCu5mu/33tS29XrfPjq2PCDxr07Va2v+2667Tkn5n/J/NW9Jv0YZ77dLaAbZocf8ve0XLut596dyW9Q3w6i1e1tL+d9pgq5b2D7D19NaMcclnn2hJv0Xb7bJh40qjsPmW67e2/82mtazvL3zhxJb1DTBr1qyW9r/NNtu0tH+ATTfdtHGlUdh66617L9o2tD/itpmZmfWerl/Q4IjbZmZm1kAvLGjaHnFb0idT/4slndrGYzUzM7MR6IV7aE4EdoyImZImAWtGxD8krQ/cLCm/mL8N8K8RMU/Sd8jO6nwp76QQcfvfU1bViNuSZpItdl4REc9IelFLj87MzMxGrRfO0BS1I+L2wcC5EfEMQET8fUxmbmZmZi3TC2doitoRcdvMzMx6TC+coWl3xO2rgXfm9+D4kpOZmVn36/oFTbsjbkfElWSLnVslLQI+1srjMzMzs9HriUtO7Yy4ncpOJft1lZmZmfWArj9DY2ZmZtaIo22bmZlZz/MZGjMzM+t5XtCYmZlZz+uJm4K7lpRdr5u9R7b/5tdl6V6HwvrZL8gXPJZlXXlrSn+apTfOSX08uyht/CKlPwd+BcAOKSf1yqEpPTClfYen+6D/6bVZuv+hsMlBANz9zGpZr0tSr5dn6XXfy9LnHvp96uWqlF4BXAvAS3kGgEMqxn11StfZL0WPOPY18OrXZ9tbZqV/WrUuAFfflcZNh/XLH2Tpo0v+mnr5ZRoz34b1eBjInmxYHPc1Kd14++nZxjteDa9L426Xlf5jcvZIoWvuS+Nem47ugix94LqnUy/XFsbNjn0K9wJwUMW46VVl6w0nw3Gp9I2pdGZWumrqdgBc/6c07o1ZeuVFWbrsxwDXp55+ntL8b70YGHgC5Osq0lmTgNl7ZTtHpnFfkUrX2xOAWx5N4/02jfCTLL15DrByQerpyoo0m2Qe6zs/zkMZeG9xVHr3vSWNt18af+OsxvKn+rIjSW/fn/9s4L214q93VxxnftzXAfAyngMG3l+vB16Vttc6KD2J4a2p9FVp3C2y99eDK7Lo7Vcvz7KvuBKuSe+tx+9IfwSurhg3e3+9mOzFOjiNmW8DbLjzetnGO1LOa9O422Tvr8f6Ngbgmt/DFdekUc7P0odu/Efq5ZqKcbP315o8kB1KYdz82LfcND1GK39/vSGNu3P2V3lhza0BuO6P8PNfZ0W/+FGW3jl3Verl+opx87/zMgAOYOh7euYaaWN2evcdkf7Ou6d03Vnc9Ejq9ebU6yVZOn9OasstFePl499MHum38j39yrzpMendd3Sa0b5phi85kNufTL3elnpNz4K//rtZ2v/39Mev8v7aihWDjjM/7vyzvcZrUhT3/P114Ovhpdm77/4X1gLgqmWp19TtNd/P0ifvyR8sn7+/riD/m2/E48DAd1U+bv7+Wn/Wi7ONt6ec17wets62H1H2bNhf/i6N+8s0yg+z9M83p/+IlN9fV5TnsDYPAQPfzfm4+ftrxow1s43jXgWvT+++nbLSZ6dsCcB1f0jj5u+vC7P0niteSL1cR+V3Vyn9wPjAinHzv/OO66SNfzkA3pRKZ6W/yrSZANyQfd1z5U0p/XGW3pY+z3ATQ9/T8wGIiN6Mtj1akk5I8Z3+KOnMTs/HzMzMxt5EOEPzfrKF8sHA7h2ei5mZmbXAuD5DI+kc4GVk563WLeS/UdJvJS2U9EspO+cnaQNJV0taJulbkh5IQTDNzMysi43rBU1EvA/4E9kl1McKRTcCe0XErsAFwCdS/qeBayNiB+BiYPM2TtfMzMxGaCJccqpmU+BCSRsBqwHpVlL2A46ELASCpMdqtDczM7MuMq7P0NRxBnBmROxEFoF7SoP6ZmZm1sUm6oJmGvDHtP0vhfx5wD8BSDqEwn03ZmZm1r0m6oLmFOAiSQuARwr5nwEOSZG93wL8BXiy/dMzMzOz4Rj399BExIy0OSf9IyIuBS6tUv0J4LURsVLS3sAeEfF8G6ZpZmZmozDuFzTDtDnwI0kl4AXgPR2ej5mZmTXB0bbNzMys503Ue2jMzMxsHPGCxszMzHqe76EZjTzadm6LlM4Edk3bO6d0m5SmYMIPpmi3eazthSldErA8C6DK/XdnEbufuT1FaF2UIuMuTJFqF2dRWjdKbV8O7EikKWThrndN0Ul3SRG8VytHqE2D5FFRd4FyiNw8DPP2Kc2CsvLM+kPnvDhtL0uPIPzdvVkk7oeXp3iviw9MlVNE8kVZ9OC1Hy2VX67tUrozf01zXpzSLCr0S1K05Cz6asXc8td5Zkp3SunWKc2CcHP3pIE556/10hRM9q4UbfYPd2XRYFcsTbGfF+6T5rwTfXdPK3ZX7n7HFDl6V5anNAtNvEOKLJ1Fp03RmDesmGs+9/z1zl+I9MI8us7Q90f+et+Rgpbf+/vshXh8WYrzu2j/1GAWLM7ebOtlwdNJcYbLUdx3SVGgd+W2NK1fM60cSTiFHJ5Urjx4zvkx7JjSrSA2HjzHfM75MdyeAp7fc//aADx0Z/Z6x5JXwcJXpEbZ8az+UPZoqPRxIcWVZ2eeSMPfnqbzG16WosQPRORNZtSY886FDtMAD60xeM7FzyPAnfln8p69eDr/PC7MP4+p4yXp85javDz1UfxM7sqtAOySImSvVo52nyI5r10x1+J7JP/DVXwea73e5c/kfZvw8B0p0vHiA1Ll/POYfTGt/Wj2/21npLbbAbvwcJrCojSlednxlT+Pv2GQ/P27a2HeDT6Ple/vpS8MfB4fuDv7DlmxJMWSXpQ+jwuzN13pDaTSIAAAIABJREFU7unFLtka2Inn01zvSFPJwtDvOOjzCKT3ES8uzLXyO7vy8zht6JzLn8cUOfre31V8Hhenz+Nt6ct18QwAXvRM+c9Y/iqbyR/SNLLP4y5k4a+nlz+T2XueSTT+PKY3X2ySpUsY+v5YWvPzmGKT55/JRduzevoPVv55zP9ztnP6btuVpSnNvqNfVo4M/gtI7//ym6vyvZ2/3lU+k9X++whwkSZutO3PSjq4cU0zMzPrVeP6DI2kvog4udPzMDMzs9bq2TM0kmZIulPSeZKWS7pY0pqS7pf0BUm3AW+RNEfS0anNqZLukLRE0pdS3hxJX5N0s6R7JR0o6TupzzmdPEYzMzNrTq+fodkG+NeImCfpO8D7U/6jEbEbgKTXpXQ9ssCT20ZESJpe6GddYG/gcGAusC/wbmC+pJkRsQgzMzPrWj17hiZ5MCLmpe0fkEXLBriwSt0ngOeAb0t6M/BMoexnkT2QZynw14hYGhH9ZHdGzmjJzM3MzGzM9PqCpvKpgPn+00MqRqwE9gQuBg5j8E8i8vAG/YXtfL/Xz2KZmZmNe72+oNk8xVwCeBuk3/lWIWkqMC0irgA+zMAP38zMzKzH9fqC5i7gA5KWk90H87U6ddcGLpO0hGzh85E2zM/MzMzaoNcvp6yMiHdU5M0o7kTE7MLunpUdFMsj4n4GHk1U2dbMzMy6VK+foTEzMzNztG0zMzPrfT5DY2ZmZj3PCxozMzPreb1+U3BH6ZQUbTsP/Nmf0tDg7cqyRvvtaFuZP6xx0wvQX6rST6GsUdt6ZVXnOIxx65UPe1xlTySqdlxNva6pbdTov5m2tcZVRVoq7Of/d0WloWXF/WJ+uSy1LZVq9z9kvHy7DeMW8yvbNjNuvdet0TyaeS1q7Y903EGvb4PxxmrcBuOV0n6fKtKSBm1Xlg3eJ6Wlcv6QOjXaTioNzc+3S7XGqxh3UqnU9Fzz4500ouPM9weOt/Ecax9vozlWO95Jhdd4OHMuaSTHOXTckRxvrf4Z+JYZxGdozMzMrOd5QWNmZmY9rycXNJI+Iun29O8/Ut5xKYr2YknfT3kbSPqxpPnp374pf09JN0laKOk3krZJ+bMlXSLpSkn3SPqfzh2lmZmZNavn7qGRNAt4J/AKsutov5U0HzgJ2CciHpH0olT9NOArEXGjpM2BXwDbAXcCr4yIlZIOBv4fcFRqMxPYlSym012SzoiIB9t1fGZmZjZ8PbegIYuo/ZOIeBpA0iXA7sBFEfEIQET8PdU9GNheKt8/tE4e0wn4rqStyG4JnVzo/5qIeCL1fQfwUsALGjMzsy7Wiwua4SgBe0XEc8VMSWcC10XEkZJmANcXiovRtlcx/l8jMzOznteL99DcABwhaU1JawFHArcCb5G0HkDhktNVwIfyhpJmps1pwB/T9ux2TNrMzMxap+cWNBFxGzAHuAX4LfCtiJgHfA74laTFwJdT9ROA3dPNwncA70v5/wN8XtJCfAbGzMys5zmW0yj4wXp+sJ4frFccL99uw7h+sJ4frOcH6/nBehV67gyNmZmZWSWfoTEzM7Oe5zM0ZmZm1vO8oDEzM7Oe51/4jIKUbgpmh2yftVPJWoi1Ut6a5bxsP6Wl9Cy/dJNTfh+j+igvMwfyBt+4p4qUvoF95TdN9TWqO3hcSmnsirxadQfGy/OqHEe9OZdUJS/t5/celuocd2WeatTNbx0r1Ks9XsqvGF+q168G7Q/pQwHpbaL8Dt/yfgzeV/nu5MJ+vbI6fdFf3h7Sh/prtKkz1yF99Vfs12479Bgq+lBUn3+V4yupIqVwQ2TqvVSxXy4v5NesQ153cF8Db2cNlKHqddJ+xVuEEqDK/lMdDTmGlF+oP/DWGn4fA3WoqFNrrhpal8Hv9Xp9lOvWOJ7yWyGfV+Hm/Yq3SfkG+HptyuXV8gozqdZ3ZV6533SEKqfZX1jpQ16ir7yt9IVXrqvBdSvrlVQaWofKNrX3S3leqUad0tD98th5m2GklXlN99FXpW3fQFmjtDIvH7c0eXJ33RQs6bMp7ECt8iMkbd/iOcyU9PrC/imSPtbKMc3MzGzsdWxBExEnR8Qv61Q5AmjZgkbSJLK4Ta9vVNfMzMy6W1suOUn6FPAO4G9kcZEWADsCl0XExZJOBQ4HVpI93feStH+ApJOAoyLi91X63RI4C9gAeAZ4T0TcKemNZMEqVwMeBd4eEX+VdAqwJfAy4A/AvsAakvYDPp+63V7S9cDmwFcj4vSxfj3MzMxsbLV8QSNpD7JI1ruQBYG8jWxBk5evRxa+YNuICEnTI+JxSXNJC5463X8DeF9E3CPpFcDZwKuAG8liOIWkdwOfAD6a2mwP7BcRz0qaDeweER9MczkF2BY4CFibLNr21yJixZi8GGZmZtYS7ThDsy9waQoQ+Zykn1WUPwE8B3xb0mXAZc10mqJm7wNcVIimvXpKNwUulLQR2Vma+wpN50bEs3W6vjwingeel/QwsCHwUDNzMjMzs87o+M+2I2IlsCdwMXAYcGWTTUvA4xExs/Bvu1R2BnBmROwEHA9MKbR7ukG/jrZtZmbWY9qxoJkHvFHSlHRW5bBiYcqbFhFXAB8muzQF8CSUfwc9RET8A7hP0ltSP5KUty1G0/6XOnOrO4aZmZn1hpYvaCJiPjAXWAL8HFhKdpkptzZwmaQlZPe+fCTlXwB8XNLCdPNvNW8H/jVF2F4GvCnln0J2KWoB8Eid6V1HdhPwIknHDPvgzMzMrCu063LKlyLiFElrAr8GFkTENwvle1Y2iIh5NPjZdkTcB7yuSv6lwKVV8k+p2P87sEed/nesN76ZmZl1h3YtaL6RHpI3BfhuRNzWpnHNzMxsAuiJaNuSziL7tVTRaRFxbifmY2ZmZt2lJxY0ZmZmZvV0/GfbZmZmZqPlZ6yMwu67fyMA+lNk00gRQaOvr2perbqV+cOpCxApAml/X2lE42Vt+4gWjEdpZUpfGJpWy2s2bUNbpblPksqRlCenhzhOqpWmesX8PJLz5Dp1avU1pG0T4w2Mm+ZMg3EKfeXbNcetM1657Qheq5rjNvFa5XWG81rlEZb7+7ON/lVRfb+c31/eb9imZh9Rp03/oP1VKY1CvWbHLbct9N3sXFf1D7Rt+vjS3IvjDvc1qj5uf1N9FF+rvKwcEbsvpZWRntP3VF9fXzmvVCoNqjPQpnofpb6+YbcZk3FLpUFzqNZHHtm6r28gKndfX6N+88jWaY6lOsc5knEb9JFH1O4rHH+11zzprmjbzZI0XdL7W9h/3ajfZmZm1v26fkEDTAeaXtCkB+yVKvL6atVvIuq3mZmZdbleWNCcCmyZHn73RUkflzRf0hJJnwGQNEPSXZK+B9wObCbpKUn/mx66t7ekk1O72yV9QykAlKQ5ko5O2/dL+oyk2yQtlbRtpw7azMzMmtcLC5oTgd9HxEzgamArsgfxzQRmSdo/1dsKODsidoiIB4C1gN9GxC4RcSNZbKc90sPy1qAiBEPBIxGxG/A14GOtOywzMzMbK72woCk6JP1bCNwGbEu2kAF4ICJuLtRdBfy4sH+QpN9KWgq8CtihxhiXpHQBMGOM5m1mZmYt1Gu/chLw+Yj4+qBMaQZDo2g/FxGrUvkU4Gxg94h4UNIpDI7AXZRH23akbTMzsx7RC2doihGxfwG8K0XoRtImkl7cRB/54uWR1PbosZ+mmZmZdUrXn4GIiEclzZN0O1m07h8CN6V7ep8C3kF2NqVeH49L+ibZDcN/Aea3dtZmZmbWTl2/oAGIiLdVZJ1WpdqgyNgRMbVi/yTgpCp9zy5szyhs3wocOOzJmpmZWdv1wiUnMzMzs7ocnNLMzMx6ns/QmJmZWc/zgsbMzMx6Xk/cFNytpCxm74tS6Khiul6VvGJaq3w9lYbkrZvSFU2kzdRp1HZlo7op0OmKUl/dsl5vu2dKs9BgWZ1yRNpBZY3S3mk7EAZtfLeV+tP2yqoprMj2U8T1UqFcWlG3bb3yRm3zcUuloX2OZLxm28LKIeO28jjHZlylNP97T0KaVN4enPYN2s//06fSpHJZqWbbwX2Q9kuDxutrrm0at1SqNtfm+hjOcRaPd+BzMby2GsFxFsdVaXCdUrOvlSbV/JtAF0bbbhTpWtIRkrYfQb8HStpndLMzMzOzXtHRBU0Tka6PAIa9oCH7ufWwFjQqLP3MzMyst7TtP+KSPkX2ELy/AQ+SxUraEbgsIi6WdCpwONk5yKvIYiodDhwg6STgqIj4fZV+TwDel9rdQRbM8n3AKknvAD4E3AmcA2yemv1HRMxLIRC2BF4G/EHSL9KYa6b8n0TEJ8b6tTAzM7Ox1ZYFjaQ9gKOAXYDJZIElFxTK1wOOBLaNiJA0PT3ddy5pwVOn+xOBLSLi+UK7c4CnIuJLqf8fAl+JiBslbU4WQmG71H57YL+IeFbSbLIo3ruSxXS6S9IZEfHgmL0YZmZmNubadYZmX+DSiHgOeE7SzyrKnwCeA74t6TLgsmH0vQQ4T9JPgZ/WqHMwsH1+ExmwTh4PCpgbEc8W6l4TEU8ASLoDeCnZGSUzMzPrUl3xs+2IWAnsCVwMHAZcOYzmbwDOAnYD5te4F6YE7BURM9O/TSLiqVRWGaX7+cK2I26bmZn1gHYtaOYBb5Q0JZ0ZOaxYmPKmRcQVwIfJLk3B4EjbQyj7HeZmEXEd8ElgGjC1SruryO6lydvNHPURmZmZWddoy4ImIuYDc8kuD/0cWEp2mSm3NnCZpCXAjcBHUv4FwMclLZS0ZZWu+4AfSFoKLAROj4jHgZ8BR0paJOmVwAnA7pKWpMtI7xv7ozQzM7NOaefllC9FxCmS1gR+DSyIiG8WyvesbBAR86jzs+2IWAHsVyX/bmDniuxjqtQ7pWJ/DjCnsH8YZmZm1vXauaD5RnpI3hTguxFxWxvHNjMzs3GsZ6JtSzqL7NdSRadFxLmdmI+ZmZl1j55Z0JiZmZnV0hU/2zYzMzMbDT9jZRTyaNvTWA2A1VM6mdWYxOoATEp5edpXkZZSvYH91QZtV08n1yyvLFN5v36+mDxoOyub1HBf5bxJFXUq0zyibV85P88rl5X3S4PyNSS/REmlIXlZqhr7eWReFfKoqMPgVAP7Q8qIVCcG71dJy5Gdy3l5pOf+Qfvk+awql5e3y3kV+ymlnL+ynF+OTszglMr88v6KQduZPLLxikH5lftoRaHshYqyFyravjAohRWFNhVlNfLzffR8nbbP12jzwsDrWPgbFzdUkVJ8L1Tm1apbmT+cutXyS6PoI98uNWhbCFw+pE6ttpX5pebq1NqvCJ5ee7/y9SjV6beZNjXqVJYX6w1p0+R+3XH7qrcZtN9Xv23V/Fr9N7PfqG7luH2F8npljfYrysp1iO6Ltt0pkuZIOrpBnf9Iv8gyMzOzLjchFzRN+g+yIJVmZmbW5bpyQSPpU5LuknSjpPMlfUzS9ZK+IOkWSXenB+YhabakMwttL5N0YNp+StJXJC2TdI2kDaqM9er04L6lkr4jafUUwXtj4DpJ17XpsM3MzGyEum5BUxGZ+1Bg90LxpIjYk+zsyaeb6G4t4NaI2AH4VWUbSVPIHqR3TETsRHZP0b9FxOnAn4CDIuKg0R2RmZmZtVrXLWgoROaOiCfJwhjkLknpAmBGE331Axem7R8w9KnC2wD3pScLA3wX2H8kkzYzM7PO6cYFTT15JOxiFOyVDD6OKXXa+6E7ZmZm41A3LmjqRuau4n5gpqSSpM0YHBOqBOS/ZnobWeDLoruAGZJenvb/mezSFDSI9G1mZmbdo+ueQxMR8yXlkbn/ytDI3JXmAfcBdwDLgWKMqKeBPSWdBDxMRYDKiHhO0juBiyRNAuYD56TibwBXSvqT76MxMzPrbl23oEnqRuaOiEdI99BEFrvh7bU6ioiPVMmbXdi+Bti1Sp0zgDNGfghmZmbWLt26oHFkbjMzM2taVy5oIuJtY9TP1LHox8zMzLqbo22bmZlZz+vGXzmZmZmZDUtXXnLqFXm07YGXsZhWy2s27fa2ecjTyQ3Ker1tX/l/K2sOJ+2ltvn2mLZNUcX7SrXTfHtSnTpj2bYyr1NtSymlmXQ4dceibbvH83F22XHmn+C1gamFbYa5X5k3mrblJ6lMvGjbw42qLWlNSZdLujPFfzq1PTM1MzOz0RjXC5omVUbV/lJEbEv2U+59JR3amWmZmZlZszq6oOm2qNoR8UxEXAcQES+QPaRv0za8FGZmZjYKHVvQdHtUbUnTgTcC1wz/6MzMzKydOnmGpmujaqcwCOcDp0fEvU2Mb2ZmZh3UrffQdDqq9jeAeyLiq6Psx8zMzNqgkwuaroyqLen/AtPILneZmZlZD+jYc2i6Mao22ULnv4A7gdskAZwZEd8azbGamZlZa3X6wXrdGFW76gN7zMzMrHt1ekHjqNpmZmY2ah1d0DiqtpmZmY0FR9s2MzOzntetP9s2MzMza1qn76HpaXm07eyHU4PTfLtUGlpWLS3Wa6ZOrXQk49Uad2idLPqq0jpYlCgVtuul1eoNp25leaPxmhm38ThKaT+lPGI0/eU8GIgkne9Xq9dMnVp9jWS8vN5wx+tTP32sSnVXDaozqbxfUV6o10ydWn2NZLy83kjGUyqLUjpDndIop/0V+wP1mqlTq6+RjDfQdvjjldP8/7qWVJHWyldzdWr11UydmuOOYLwh46bC9N1F+u4akpb6mqtTq69m6tTqayTj5WlFncrv7vw/7cXvbmlygzq1+2qmTvXygXGHM16+X7tOF0bblvQSSRdI+r2kBZKukLS1pEjPg8nrrS9pRR7LSdIpkv4oaZGkOyQd27mjMDMzs07rZCwnAT8Bro+ILSNiFvCfwIZkz5t5Q6H6W4BlFV18JSJmAm8Cvq6BZaCZmZlNMJ08Q3MQsCIi8gfcERGLgQeBZ4DlkvKAlccAP6rWSUTck+qvC5CidX9F0q2SlkvaQ9Ilku6pOOvz03RWaJmk9xbyG0buNjMzs+7SyQXNjmTBJ2u5AHhrCnOwiiwq9hCSdiOLu/RwIfuFiNid7GnAlwIfSOPNlrReqvOudFZod+CEQn7dyN1mZmbWfbr5V05XAq8B3spAJO2iD0taBvwW+FxF2dyULgWWRcSfI+J54F5gs1R2gqTFwM0pb6uU3yhyt5mZmXWZTi5olgGzahVGxAtkZ3A+ClxcpcpX0lmUo4BvSypG386jdfcXtvP9SZIOBA4G9o6IXYCF1I7e7Qf1mJmZdblOLmiuBVavuH9lZwbOoAD8L/DJiPh7rU4iYi5wK/Avwxh7GvBYRDwjaVtgr0JZo8jdZmZm1mU6tqBJwSaPBA5OP9teBnwe+EuhzrKI+G4T3X0W+IikZo/nSrIzNcuBU8kuO+XyyN23A69KfZuZmVkX63Qspz8B/1SlaMcqdecAc9L2KRVlC4Bt0u6BhfzrgesL+wcWmh1aZ15DInebmZlZ9+rmm4LNzMzMmuIFTQVH7jYzM+s9jrZtZmZmPc9naMzMzKznOdr2KJSjbedRmZVHa1Z5uxzRWUppZX5FSmmgnxophbpDyivrlqq3Haingf1S9TrlCLbV9ivKorxfGfVWg8tLqpJHRf95eWV+lbzyPuU6xf0olmd/tvLhDLSJwfspWrE0sD0ob9B+3meVfQ3OG3hJompaStGSpaBUWVZ++aJ+SlTJy/RV5Pflh6IYtF0s66tsW5kP9CnfVvW2Q/JVTvO8SYW8wWmpen6UqtSprDv4M9dHib40Yl9UlvXV3c9aDs3LXrO+wfsVqegbUkfpK7ikgTpAIbJ9vj9paJkG90Fl/qAozZOq5FGI2lyZlobkRalQVi+/VCLKZYO/h0LV94v1olw2+Dsk/56IGt85UYi2PbRu9e+SKET3jsL3S1anIr/ad0yD753K/Pz7ARW+f6qUFQ6v/F2j4vdWxfeAVFl3cB8lxZCyIV/V1MiXGPLSSIPqDrxE+X/nVO5zoK4G1ancV5Xy8mes3Ef5HEz3RduuRdKBki4bZpv7Ja0/kjEkHS7pxOHO08zMzLqDz9BQfjjf3IYVzczMrCu19QyNpOMkLZG0WNL3Jc2RdHSh/KlC9XUkXS7pLknn5A/Nk3SIpJsk3SbpIknFXyV9KOUvTU8ARtJakr4j6RZJCyW9qcq8Zks6M21fKum4tH28pPNa8VqYmZnZ2GnbgkbSDsBJwKtS/KR/b9BkT+BDwPbAlsCb0yWlk4CDI2I3spAHxYfgPZLyvwZ8LOX9F3BtROwJHAR8UdJadcZ9L3CypFeSxZH60DAO08zMzDqgnZecXgVcFBGPAETE38s3pFZ3S0TcCyDpfLKo18+RLXDmpbarATcV2lyS0gXAm9P2IcDhkvIFzhRg81qDRsRfJZ0MXAccWS+OlJmZmXWHTt9Ds5J0lihdUlqtUFb5gJwgu7P56og4tkZ/eWTtVQwcm4CjIuKuYkVJG9aZ107Ao8DGjQ7AzMzMOq+d99BcC7xF0noAkl4E3A/MSuWHA5ML9feUtEVa6BxDFvX6ZmBfSS9PfawlaesG4/6C7N4apTa71qssaU+yOE+7Ah+TtEXzh2hmZmad0LYFTUQsAz4H/ErSYuDLwDeBA9L+3mSRrnPzgTOB5cB9wE8i4m/AbOB8SUvILjdt22Do/yZbKC1JEb3/u1ZFSaunOb0rBc78KPAdNbg2ZmZmZp3l0Aej4Afr+cF6frDeQOoH6/nBelmffrCeH6znB+uZmZmZjYgXNGZmZtbzfMnJzMzMep7P0JiZmVnP6/RzaHqalD0rp0R2E2cxrZbXbNrtbZXSviptimXjpW2J/ibqrEpp9HTboa9Jrf5XVexHb7VNtxT2l2qkeXnf0PKabZpIG9ZJ465K48YIxl1VGkHbKuMO9/iK4zbdtk3jDnlNCn/faq9X3baFdNhtOzhu/l4eybjNzKmd4wYxsW8KljRD0u2dnoeZmZmNvQmzoGmGyr9pNDMzs14y0RY0kySdJ2m5pIslrSnpfklfkHQb2ZOM90gRwRdJ+qLP6piZmXW/ibag2QY4OyK2A/4BvD/lPxoRu0XEBcC5wPERMRPSRXczMzPrahNtQfNgRMxL2z8gi+ANcCGApOnA2hGRR/D+YZvnZ2ZmZiMw0RY01SJ4w+AYUmZmZtZjJtqCZnNJe6ftt5FF8C6LiMeBJyW9ImW9tZ2TMzMzs5GZaAuau4APSFoOrAt8rUqdfwW+KWkRsBbwRBvnZ2ZmZiMwYR6sFxH3A9tWKZpRsb8sInYGkHQicGtrZ2ZmZmajNWEWNMPwBkn/SfbaPADM7ux0zMzMrBEvaCpExIWkXz2ZmZlZb3C0bTMzM+t5E+2mYDMzMxuHfMlpNKTs9NbktL9aIV2tSl4z6eRRtK02brW5Ndu23hyH2yal/alt/ySI9O7Lo7GuTOkLNE5rla0YRdt6fQ63TbXxmpnbcOfaT/aiRfoo9w9KR/IGGs4bpjJt95tvuG3rHOeq9GbsxjffSNsW0xa8+ZSeo15aOTTt9NdfN7/z8jTvb1I5GvzKGmm1P14vvfla8A0Yf5m40bYdadvMzGx8mxALGjMzMxvfJtKCpk/SNyUtk3SVpDUknSDpjhRd+wJJpRR9e3reSNI9kjbs5MTNzMysvom0oNkKOCsidgAeB44CTgR2TQ/Se19E9AOXAkcCpBAID0TEXzs0ZzMzM2vCRFrQ3BcRi9L2ArInBC8BzpP0Dkh3YGXPoDkmbb8VP5PGzMys602kBc3zhe1VZL/wegNwFrAbMF/SJOAm4OWSNgCOAC5p90TNzMxseCbSgqZSCdgsIq4DPglMA6ZG9qTBnwBfBpZHxKMdnKOZmZk1YSI/h6YP+IGkaYCA0yPi8VR2ITAfx3EyMzPrCRNiQZMibe9Y2P9Sg/q3ki1yzMzMrAdM5EtOZmZmNk54QWNmZmY9z9G2zczMrOf5DI2ZmZn1vAlxU3DLaLt0eiuPIlqMJlotr7Cfh6qtFsp1cpW8evvV2tarU2t/JG1GMsfRjFerbcV+pLRanNcGf5kxaVOtbb06tfZHMl6+347x6v9RRvMHbXXb0XxQ2tg2D0E/nD9Op970I3kjdXjcvmj+nTYWX9Uj+eocwddf18w1ixg+kjdBvl+jThw4caNtm5mZ2fg2JgsaSZ+VdHCd8iMkbT9GYx0u6cQGdQ6UdNlYjGdmZmbdb0wuOUXEyQ2qHAFcBtzRTH+SJkXEymplETEXmDu8GZqZmdl4NuwzNJI+JekuSTdKOl/SxyTNkXR0Kj9V0h2Slkj6kqR9gMOBL0paJGnLGv1eL+mrkm4F/l3SGyX9VtJCSb+UtGGqN1vSmWl7jqTTJf1G0r35HJJ1JF2e5nqOpFJqc6ykpZJul/SFlPcWSV9O2/8u6d60/TJJ84b7GpmZmVl7DesMjaQ9gKOAXcju+7mNLHJ1Xr4ecCSwbUSEpOkR8bikucBlEXFxgyFWi4jdU1/rAnulft4NfAL4aJU2GwH7AduSnbnJx9gT2B54ALgSeLOk3wBfAGYBjwFXSToCuCH1D/BK4FFJm6TtXzf36piZmVmnDPeS077ApRHxHPCcpJ9VlD8BPAd8O93DMtz7WC4sbG8KXChpI7Kbp++r0eanEdEP3JGfxUluiYj8TMv5ZIueFcD1EfG3lH8esH9E/FTSVElrA5sBPwT2J1vQONq2mZlZlxvTXzml+172JDtLchjZmZHheLqwfQZwZkTsBBwPTKnR5vnCdvGnXJVPDGz0BMHfAO8E7iI7Y/NKYG/Al5zMzMy63HAXNPOAN0qaImkq2aKlLOVNi4grgA+TXZoCeBJYe5hjTQP+mLb/ZZhtAfaUtEW6d+YY4EbgFuAASetL6gOOBX6V6t8AfIzsEtNC4CDg+Yh4YgRjm5mZWRsNa0ETEfPJ7lNZAvwcWEp2mSm3NnCZpCVkC4iPpPwLgI+nG3yr3hRcxSnARZIWAI8MZ57JfOBMYDnZ5aqfRMSfgRPF4YyKAAANl0lEQVSB64DFwIKIuDTVv4HsctOvI2IV8GA6BjMzM+tyI/nZ9pci4hRJa5KdzVgQEd8slO9Z2SAi5pHdoFtTRBxYsX8pcGmVenOAOWl7dkXZ1JReT3YPTLVxzgfOr5L/ewqXrCLikHrzNTMzs+4xkgXNN9JD8qYA342I28Z4TmZmZmbD0vZo25LOIvu1VNFpEXFuWydiZmZm40bbFzRmZmZmY83RtkfhFGU/Be/vyxaF/Skwbn/f4O2q6aTa5bXbRsM+atZt1FczbUtDyxu3qcwvtK3SX9025fpV6tTcr2wbA9u12qTySPulvqCU8kp5XjltnN90XVXmByXVaKMGbRVD61b2pcq+Ymhe3mZI/tB0SB4N2hTKh9Rtdp+omlc97R9o07BujbZRpW1U7vfXLB/Y7h9cVplWKR/YbtC2Snmpv0abOvkD2xX99tfoo7/KeLXa9tdo29/fVJ1a+6VV2bZSGeU0y2dVxX5/wKr+wXWHs1+rrHKcVXXaViur1ldxv7w9kjaN6lbJr6yzsok2jcZd2cR8apVFjJ9o25K+1SjYZTEcg5mZmY1vXXuGRpLILon1V5ZFxLs7MCUzMzPrUl11hkbSjBRM8nvA7WQhFG6VtEzSZwr1rpeUx3x6StLnJC2WdHNF+IODU/u7JR2W6k+RdG4KULlQ0kEp/3JJO6fthZJOTtuflfSeNr0EZmZmNgJdtaBJtgLOjogdgI+mYJU7kz3hd+cq9dcCbo6IXciei1NcfMwgey7OG4BzJE0BPgBECqlwLPDdlH8D8EpJ04CVDPwSywEqzczMulw3LmgeiIib0/Y/SbqNLBTBDlR/ON8LDATBXEC2iMn9KCL6I+Ie4F6yiNz7AT8AiIg7yaJxb022oNmfbCFzOTA1PTxwi4i4a+wOz8zMzMZaN95D8zSApC3IYivtERGPSZpD9QCVK2Lgt+erGHxMUVG3cr9oPrA72cLnamB9srM9C4Z7AGZmZtZe3XiGJrcO2eLmiXRfzKEj6OMtkkopftTLGIik/XYASVsDmwN3RcQLZPGb3gLcxOBglWZmZtbFuvEMDQARsVjSQuBOsoXGvBF08weyCNvrAO+LiOcknQ18TdJSsntlZkfE86n+DcCrI+JZSTcAm6Y8MzMz62JdtaCJiPuBHQv7s2vUO7CwPbWwfTFwcYO2zwHvrFH2KeBTaftPFIJVmpmZWffq5ktOZmZmZk3xgsbMzMx6noNTmpmZWc/zGRozMzPreV11U3CvkU5Jp7cmp5z85ZxcsV1Z1mh/JG3y/VplzfSRbze4F3pSIZ1UJa/ZtJfadv1c01tx0sqUrqI0aRUAfeU0K5s0JD+lfavoI9Uh5Q1Ja5c3blu7j2b6r9XHcObY/FzHw3GuLO83PM5VaX9lnvbTN/BWAkBpnzxdVbFfzK/Ma6ZNvj+SNnlaq+5I2jTT10ja5PsjOb5hzjlSunIVrMi3U7qiUAawgsHpysL+yjpljfZH0ibfr1V2yniKtj1WJP2mTtl0Se9v53zMzMxsZCb0giYi9qlTPB3wgsbMzKwHTOgFjaSnUvpxSfMlLSlE9T4V2FLSIklf7NwszczMrJEJfw+NpEPIInzvSXbzyFxJ+wMnAjtGxMxOzs/MzMwam/ALGuCQ9G9h2p9KtsD5Q8dmZGZmZsPiBU12VubzEfH1QZnSjI7MxszMzIZtQt9Dk/wCeJekqQCSNpH0YuBJYO2OzszMzMyaMtEXNBERVwE/BG5KEbgvBtaOiEeBeZJu903BZmZm3W3CXnKStB7wd4CIOA04rbJORLyt3fMyMzOz4ZuQZ2gkbQzcBHyp03MxMzOz0ZuQZ2gi4k/A1p2eh5mZmY0NR9s2MzOznjchLzmZmZnZ+DIhLzmNFUkBsAZrkqVrAbAma5a3i3nF/Xr5ed7qrJGNk6Jfl1KqtA6tlq/ydl42uG5l/oq0/zQlnilvD+QBdfMb1e1vdRjqNRicrknj/Gbrrp7SvvQPBv4vQF9FWi+/Vt1Sf0pTLFlVpKWV1fNq1a3MVx56tzLtr5G/qk5Zjfz+Z7I0ns7+VeYV03r5lXnxfJaO5vWtlz/Sv2ffCNqMxbhVjnOdtDuN6vvF/Gp5teoCTI1CAPf0py/vN5HfqG5f2s/foqXCfrW8WnUr8yvzaka9LqbN1KmWPpX+MYL0ydpl8VyW1vvkDfNTSn+VOlFjv1r+cOoCMHVqlk6bBuuum21Pnz78tEbZrFmzHG3bzMzMxqcRL2gkfVbSwWM5mVaRdISk7UfQbrakM1sxJzMzMxs7I17QRMTJEfHLsZxMCx0BVF3QSPJlNzMzsx7XcEEjaYak5ZK+KWmZpKskrSFpjqSjU537Jf2PpKWSbpH0cklrS7pP0uRUZ53ifpVxTpB0h6Qlki5IeadI+r6kmyTdI+k9hfoflzQ/1f9MIf+4lLc4td0HOBz4oqRFkraUdL2kr0q6Ffh3SW+U9FtJCyX9UtKGo3pVzczMrK2aPTuxFXBsRLxH0o+Ao6rUeSIidpJ0HPDViDhM0vXAG4CfAm8FLomIFTXGOBHYIiKelzS9kL8zsBewFrBQ0uXAjmlOe5IFl5wraX/gUeAkYJ+IeETSiyLi75LmApdFxMUAkgBWi4jd0/66wF4REZLeDXwC+GiTr42ZmZl1WLMLmvsiYlHaXgDMqFLn/EL6lbT9LbLFwU+BdwLvqdIutwQ4T9JPU/3cpRHxLPCspOvIFjH7AYcAC1OdqWQLnF2AiyLiEYCI+Hud8S4sbG8KXChpI2A14L467czMzKzLNHsPzfOF7VVUXwhF5XZEzANmSDoQ6IuI2+uM8QbgLGA3YH7h3pbKJ/8F2VmZz0fEzPTv5RHx7SaPJfd0YfsM4MyI2Ak4HpgyzL7MzMysg8byZ9vHFNKbCvnfI4tmfW6thpJKwGYRcR3w/9u7lxA5qiiM4/+T6Z4ZJDEPxY0rd4oL3ZhNFKJkY1BEiQtFVFzoSsGgZBM1vkAxm/gCMwoJKgYMQlTUIPgiQSQYcRIXuhJBVwEjUZMee3Jc1LnV1dVV3ZMxme6O3w+GW/fcW9XdM81w6a6qbwvZbRHiQnZuMbPpCJNcDxwC9gP3mdny2P9SM7sE+Ay4PeZiZmviGCeAFX2e+0rg19i+Z/BLFRERkVFyNq/wWW1ms2Sf5txRqL8NPEPnK6kqE8BbZraS7NOXF939eJzrMgt8DlwMPB05TL+Z2RXA1zHnT+Aud//BzJ4FvjSzebKvpO4F9gAzZvYQsKni8bcB75rZ72SLossW8fpFRERkSAYuaNz9Z7KTcFO/LqH6BXffUlG/Ftjr7sf7PMY/Ma/KrLvfXbHPDmBHRX03sLtUO0j3ZdvrS+P7gH0Vx9oF7Kp73iIiIjIazuk9WMzsJeBGYOO5fBwRERH5f1vytG0zewVYVyrvcPfac2xERERE+lnyBY2IiIjI2abb/v8HZk9mq8GpSBGeOkneny5sF8fq6qk/fbK3Nhdppa2432BrdXc7V6gvZE5Xu6rzGBdGLUXuLqSti/yta1OidTN+oDdMu1yvmpfXYkHenIt+3GGgEf38jgPR91ZpuzDH5/r0y8eLv01+9X+pb4V+vt1nTqE/Gf1J/mZqPmqR8JvaqdSfr6m3Yao0VrtvpDcvm8h+AJY1OrXKtmK8d2wi2qzQjLYRd2Roxh+0QaNruzhWVy/2O9vtGGv37TdpD5zT05+P/uk2zfmUNJ41tVHHVf1Bc/N6hAmftk6/uF0eG9Qvj0WiM6e8vj3ZZ6zYVs1L2+k2qqltU10vjvcbq9w3/m+11wDpwtao5f1+9UH7ZG0r3s+teB+3GtCK93wr3vN1/bmKemc7+121JrN2srY9nfdTrZnGmr1zym3azu/V37DoW1fdok6hn+ZQmpPvk8ar6o3uOeV9yeulYzWtp5bvO21K2xYREZHz00gtaAYleC82NVtERETObyO1oFlAgndtava5pERuERGR0Ta0BY2ZPWZmP5rZATN7x8weKSV4P1dI395elZpdc9wvzOz5SP3+ycyui/pEHOdoHPPBqD8eqd1HzWynxZ36yoncS/JLERERkUUZyicPZnYNWWL3VWSnGR0mC71M4xcBtwKXRwL2qrhzcFdqdh8Nd19rZhuBJ4ANwP1koZpXu3u7EIvwsrs/FY/7JnAT8EGM5YncIiIiMrqG9QnNOrIU7VPufoLOAiL5g+w8/DfM7DY6l4cs1HvRFpPBNwCvuXsbupK4rzezb8zsCHADcGXhOMVEbhERERlRI3UOTRKLjrXAXrJPTD45w0Oka2vrksEBMLNp4FVgUyRtz9CdtP1X5Y4iIiIyUoa1oDkI3Bwp2svJFi25qK1094+Ah8m+moLBqdn9fAo8kE7wja+c0uLlWDxmVXCliIiIjLihLGjc/RDwPlmS9sfAEbKvmZIVwIeR3n0A2Bz1PcCjZvZd3UnBfbwO/ALMmtn3wJ0RmDkDHAX2A4cW+ZJERERkiIZ5OfJ2d99mZhcAXwHfuvtMYXxteYeK1Owe7r6+sH2MOIcmvsbaTGdxlOZsBbb2O46IiIiMtmEuaHbGTfKmgd3ufniIz0VERETG2NiGUyq1W0RERJKxXdCIiIiIJCN52baIiIjImdCCRkRERMaeFjQiIiIy9rSgERERkbGnBY2IiIiMvX8BfFW03ZfhtIgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x1152 with 79 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "==================\n",
    "Colormap reference\n",
    "==================\n",
    "\n",
    "Reference for colormaps included with Matplotlib.\n",
    "\n",
    "This reference example shows all colormaps included with Matplotlib. Note that\n",
    "any colormap listed here can be reversed by appending \"_r\" (e.g., \"pink_r\").\n",
    "These colormaps are divided into the following categories:\n",
    "\n",
    "Sequential:\n",
    "    These colormaps are approximately monochromatic colormaps varying smoothly\n",
    "    between two color tones---usually from low saturation (e.g. white) to high\n",
    "    saturation (e.g. a bright blue). Sequential colormaps are ideal for\n",
    "    representing most scientific data since they show a clear progression from\n",
    "    low-to-high values.\n",
    "\n",
    "Diverging:\n",
    "    These colormaps have a median value (usually light in color) and vary\n",
    "    smoothly to two different color tones at high and low values. Diverging\n",
    "    colormaps are ideal when your data has a median value that is significant\n",
    "    (e.g.  0, such that positive and negative values are represented by\n",
    "    different colors of the colormap).\n",
    "\n",
    "Qualitative:\n",
    "    These colormaps vary rapidly in color. Qualitative colormaps are useful for\n",
    "    choosing a set of discrete colors. For example::\n",
    "\n",
    "        color_list = plt.cm.Set3(np.linspace(0, 1, 12))\n",
    "\n",
    "    gives a list of RGB colors that are good for plotting a series of lines on\n",
    "    a dark background.\n",
    "\n",
    "Miscellaneous:\n",
    "    Colormaps that don't fit into the categories above.\n",
    "\n",
    "\"\"\"\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "# Have colormaps separated into categories:\n",
    "# http://matplotlib.org/examples/color/colormaps_reference.html\n",
    "cmaps = [('COLOR MAP', [\n",
    "            'viridis', 'plasma', 'inferno', 'magma',\n",
    "            'Greys', 'Purples', 'Blues', 'Greens', 'Oranges', 'Reds',\n",
    "            'YlOrBr', 'YlOrRd', 'OrRd', 'PuRd', 'RdPu', 'BuPu',\n",
    "            'GnBu', 'PuBu', 'YlGnBu', 'PuBuGn', 'BuGn', 'YlGn',\n",
    "            'binary', 'gist_yarg', 'gist_gray', 'gray', 'bone', 'pink',\n",
    "            'spring', 'summer', 'autumn', 'winter', 'cool', 'Wistia',\n",
    "            'hot', 'afmhot', 'gist_heat', 'copper',\n",
    "            'PiYG', 'PRGn', 'BrBG', 'PuOr', 'RdGy', 'RdBu',\n",
    "            'RdYlBu', 'RdYlGn', 'Spectral', 'coolwarm', 'bwr', 'seismic',\n",
    "            'Pastel1', 'Pastel2', 'Paired', 'Accent',\n",
    "            'Dark2', 'Set1', 'Set2', 'Set3',\n",
    "            'tab10', 'tab20', 'tab20b', 'tab20c',\n",
    "            'flag', 'prism', 'ocean', 'gist_earth', 'terrain', 'gist_stern',\n",
    "            'gnuplot', 'gnuplot2', 'CMRmap', 'cubehelix', 'brg', 'hsv',\n",
    "            'gist_rainbow', 'rainbow', 'jet', 'nipy_spectral', 'gist_ncar'])]\n",
    "\n",
    "\n",
    "nrows = max(len(cmap_list) for cmap_category, cmap_list in cmaps)\n",
    "gradient = np.linspace(0, 1, 256)\n",
    "gradient = np.vstack((gradient, gradient))\n",
    "\n",
    "\n",
    "def plot_color_gradients(cmap_category, cmap_list, nrows):\n",
    "    fig, axes = plt.subplots(nrows=nrows, figsize=(8, 16))\n",
    "    axes[0].set_title(cmap_category + ' colormaps', fontsize=14)\n",
    "    fig.subplots_adjust(top=0.97, bottom=0.01, right=0.98, left=0.15)\n",
    "    for ax, name in zip(axes, cmap_list):\n",
    "        ax.imshow(gradient, aspect='auto', cmap=plt.get_cmap(name))\n",
    "        pos = list(ax.get_position().bounds)\n",
    "        x_text = pos[0] - 0.01\n",
    "        y_text = pos[1] + pos[3]/2.\n",
    "        fig.text(x_text, y_text, name, va='center', ha='right', fontsize=10)\n",
    "\n",
    "    # Turn off *all* ticks & spines, not just the ones with colormaps.\n",
    "    for ax in axes:\n",
    "        ax.set_axis_off()\n",
    "\n",
    "\n",
    "for cmap_category, cmap_list in cmaps:\n",
    "    plot_color_gradients(cmap_category, cmap_list, nrows)\n",
    "plt.savefig('figs/map.pdf')\n",
    "plt.show()"
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